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Data Acquisition Toolbox™ User’s Guide

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Revision History

May 1999 First printing New for Version 1 November 2000 Second printing Revised for Version 2 (Release 12) June 2001 Third printing Revised for Version 2.1 (Release 12.1) July 2002 Online only Revised for Version 2.2 (Release 13) June 2004 Online only Revised for Version 2.5 (Release 14) October 2004 Online only Revised for Version 2.5.1 (Release 14SP1) March 2005 Online only Revised for Version 2.6 (Release 14SP2) September 2005 Online only Revised for Version 2.7 (Release 14SP3) October 2005 Reprint Version 2.1 (Notice updated) November 2005 Online only Revised for Version 2.8 (Release 14SP3+) March 2006 Fourth printing Revised for Version 2.8.1 (Release 2006a) September 2006 Online only Revised for Version 2.9 (Release 2006b) March 2007 Online only Revised for Version 2.10 (Release 2007a) May 2007 Fifth printing Minor revision for Version 2.10 September 2007 Online only Revised for Version 2.11 (Release 2007b) March 2008 Online only Revised for Version 2.12 (Release 2008a) October 2008 Online only Revised for Version 2.13 (Release 2008b) March 2009 Online only Revised for Version 2.14 (Release 2009a) September 2009 Online only Revised for Version 2.15 (Release 2009b) March 2010 Online only Revised for Version 2.16 (Release 2010a)

Introduction to Data Acquisition

Product Overview ................................. 1-2

Understanding Data Acquisition Toolbox Software Exploring the Toolbox Supported Hardware

.............................. 1-3

............................... 1-4

...... 1-2

Contents

Anatomy of a Data Acquisition Experiment

System Setup Calibration Trials

Data Acquisition System

Overview Data Acquisition Hardware Sensors Signal Conditioning The Computer Software

Analog Input Subsystem

Function of the Analog Input Subsystem Sampling Quantization Channel Configuration Transferring Da ta from Hardware to System Memory

Making Quality M easurements

What Do You Measure? Accuracy and Precision Noise Matching the Sensor Range and A/D Converter Range How Fast Should a Signal Be Sampled?

........................................... 1-6

........................................... 1-38

..................................... 1-5

....................................... 1-5

........................... 1-7

........................................ 1-7

......................... 1-10

.......................................... 1-11

............................... 1-15

.................................... 1-17

......................................... 1-17

........................... 1-20

.............. 1-20

........................................ 1-20

..................................... 1-24

............................. 1-28

...................... 1-34

............................ 1-34

............................. 1-34

............... 1-40

.......... 1-5

... 1-31

... 1-40

Getting Comm and-Line Function Help

.............. 1-45

Selected Bibliography .............................. 1-46

Using Data Acquisition Toolbox Software

Installation In formation ........................... 2-2

Prerequisites Toolbox Installation Hardware and Driver Installation

..................................... 2-2

............................... 2-2

.................... 2-3

Toolbox Components

Information and Interaction MATLAB F unctions Data Acquisition Engine Hardware Driver Adaptor Supported Hardware Unsupported Hardware

Accessing Your Hardware

Connecting to Your Hardware Acquiring Data Outputting Data Reading and Writing Digital Values Acquiring Data in a Loop

Understanding the Toolbox Capabilities

Contents File Documentation Examples Quick Reference Guide Demos

Examining Your Hardware Resources

Using the daqhwinfo Function General Toolbox Information Adaptor-Specific Information Device Object Information

..................................... 2-19

.......................................... 2-20

............................... 2-4

......................... 2-4

............................... 2-6

............................ 2-6

........................... 2-9

............................... 2-9

............................ 2-11

.......................... 2-12

....................... 2-12

................................... 2-12

.................................. 2-13

.................. 2-14

........................... 2-17

........................... 2-19

............................. 2-20

....................... 2-21

........................ 2-21

........................ 2-22

.......................... 2-23

............. 2-19

............... 2-21

vi Contents

Getting Help

...................................... 2-25

The daqhelp Function .............................. 2-25

The propinfo Function

.............................. 2-25

Data Acquisition Session

Understanding the Data Acquisition Session ......... 3-2

Overview Real-Time Data Acquisition Example: The Data Acquisition Se ssion

........................................ 3-2

......................... 3-3

............... 3-4

Creating a Device Object

Understanding Device Objects Creating an Array of Device Objects WhereDoDeviceObjectsExist?

Hardware Channels or Lines

Adding Channels and Lines Mapping Hardware Channel IDs to the MATLAB

Indices

Configuring an d Returning P roperties

Overview Property Types Returning Property Names and Property Values Configuring Property Values Specifying Property Names Default Property Values The Property Inspector

Acquiring a nd Outputting Data

Device Object States Starting the Device Object Logging or Sending Data Stopping the Device Object

........................................ 3-12

........................................ 3-14

................................... 3-14

........................... 3-6

....................... 3-6

.................. 3-7

...................... 3-8

....................... 3-10

......................... 3-10

.............. 3-14

........................ 3-20

......................... 3-22

............................ 3-22

............................. 3-23

..................... 3-24

............................... 3-24

.......................... 3-25

........................... 3-25

.......................... 3-26

........ 3-16

Cleaning Up

....................................... 3-28

vii

Getting Started with Analog Input

Creating an Analog Input Obje ct .................... 4-2

Adding Channels to an Analog Input Object

Channel Group Referencing Individual Hardware Channels Example: Adding Channels for a Sound Card

Configuring Analog Input Properties

Analog In pu t: Basic Properties The Sampling Rate Trigger Types The Samples to Acquire per Trigger

Acquiring Data

Starting the Analog Input Object Logging Data Stopping the Analog Input Object

Analog Input Examples

BasicStepsforAcquiringData Acquiring Data with a Sound Card Acquiring Data with a National Instruments Board

Evaluating the Analog Input Object Status

Status Properties The Display Summary

................................... 4-4

................ 4-9

...................... 4-9

................................ 4-10

.................................... 4-12

.................. 4-13

.................................... 4-14

..................... 4-14

..................................... 4-14

.................... 4-15

............................ 4-16

...................... 4-16

................... 4-16

.................................. 4-24

............................. 4-25

.......... 4-4

............ 4-6

........... 4-7

..... 4-20

........... 4-24

viii Contents

Doing More with Analog Input

Configuring and Sampling Input Channels .......... 5-2

Properties Associated with Configuring and Sampling Input

Channels

Input Channel Configuration

...................................... 5-2

........................ 5-2

The Sampling Rate ................................ 5-4

Channel Skew

.................................... 5-7

Managing Acquired Data

Analog Input Data Management Properties Previewing Data Rules for Using peekdata Extracting Data from the Engine Returning Time Information

Configuring Analog Input Triggers

Analog Input Trigger Properties Defining a Trigger: Trigger Types and Conditions Executing the Trigger Trigger Delays Repeating Triggers How Many Triggers Occurred? When D id the Trigger Occur? Device-Specific Hardware Triggers

Events and Callbacks

Understanding Events and Callbacks Event Types Recording and Retrieving Event Information Creating and Executing Callback Functions Examples: Using Callback Properties and Functions

.................................. 5-10

.................................... 5-28

...................................... 5-46

........................... 5-10

............ 5-10

........................... 5-11

..................... 5-13

........................ 5-18

.................. 5-21

..................... 5-21

.............................. 5-27

................................ 5-32

....................... 5-37

........................ 5-38

................... 5-39

.............................. 5-46

................. 5-46

............ 5-53

....... 5-22

........... 5-49

.... 5-55

Linearly Scaling the Data: E ngineering Units

Analog Input Engineering Units Properties Example: Performing a Linear Conversion Linear Conversion with Asymmetric Data

........ 5-58

............ 5-58

............. 5-60

............. 5-61

Analog Output

Getting Started with Analog Output ................. 6-2

Creating an Analog Output Object Adding Channels to an Analog Output Object Configuring Analog Output Properties

................... 6-2

.......... 6-3

................ 6-5

Outputting Data .................................. 6-7

Analog Output Examples Evaluating the Analog OutputObjectStatus

........................... 6-9

........... 6-12

Managing Output Data

The Analog Output Subsystem Queuing Data with putdata Example: Queuing Data with putdata

Configuring Analog Output Triggers

Analog O utput Trigger Properties Defining a Trigger: Trigger Types Executing the Trigger How Many Triggers Occurred? When D id the Trigger Occur? Device-Specific Hardware Triggers

Events and Callbacks

Understanding Events and Callbacks Event Types Recording and Retrieving Event Information Examples: Using Callback Properties and Callback

Functions

Linearly Scaling the Data

Engineering Units Example: Performing a Linear Conversion

...................................... 6-26

...................................... 6-32

............................. 6-16

...................... 6-16

......................... 6-16

................. 6-18

................ 6-20

.................... 6-20

.................... 6-21

.............................. 6-22

....................... 6-22

........................ 6-23

................... 6-24

.............................. 6-26

................. 6-26

.......................... 6-35

................................. 6-35

............. 6-36

........... 6-29

x Contents

Starting Multiple Device Objects

Advanced Configurations Using Analog Input

Starting Analog Input and Analog Output

Simultaneously

.................................. 7-2

.................... 6-39

and Analog Output

Synchronizing Analog Input and Analog Output Using

RTSI Hardware

................................. 7-4

Digital Input/Output

Digital I/O Objects ................................. 8-3

Creating a Digital I/O Object The Parallel Port

.................................. 8-4

........................ 8-3

Adding Lines to a Digital I/O Object

Using the Addline Function Line and Port Characteristics Referencing Individual Hardware Lines

Writing and Reading Digital I/O Line Values

Writing Digital Values Reading Digital Values Example: Writing and Reading Digital Values

Generating Timer Events

Overview Timer Events Starting and Stopping a Digital I/O Object Example: Generating Timer Events

Evaluating the Digital I/O Object Status

Running Property The Display Summary

........................................ 8-21

..................................... 8-21

................................. 8-25

......................... 8-7

....................... 8-9

............................. 8-16

............................. 8-18

........................... 8-21

............................. 8-25

................. 8-7

............... 8-13

............. 8-22

.................. 8-23

............. 8-25

......... 8-16

.......... 8-19

Saving and Loading the Session

Saving and Loading Device Objects ................. 9-2

Saving Device Objects to a File

...................... 9-2

Saving Device Objects to a MAT-File .................. 9-4

Logging Information to Disk

Analog Input Logging Properties Specifying a Filename Retrieving L ogg ed Information Example: Logging and Retrieving Information

.............................. 9-6

........................ 9-5

..................... 9-5

...................... 9-7

.......... 9-9

softscope: The Data Acquisition Oscilloscope

Oscilloscope Overview ............................. 10-2

Opening the Oscilloscope Hardware Configuration

Displaying Channels

Creating a Display Creating Additional Displays Configuring Display Properties Math and Reference Channels Removing Channel Displays

........................... 10-2

............................ 10-3

............................... 10-5

................................ 10-5

........................ 10-6

...................... 10-8

....................... 10-9

......................... 10-12

xii Contents

Channel Data and Properties

Scaling the Channel Data Configuring Channel Properties

Triggering the Oscilloscope

Acquisition Types Trigger Types Configuring Trigger Properties

Making Measurements

Predefined Meas ure m ent Defining a Measurement Defining a New Measurement Type Configuring Measurement Properties

Exporting Data

................................. 10-18

.................................... 10-18

.................................... 10-28

........................... 10-14

............................. 10-21

........................... 10-21

........................... 10-22

....................... 10-14

..................... 10-15

........................ 10-18

...................... 10-20

................... 10-24

................. 10-25

Channels ........................................ 10-28

Measurements

.................................... 10-29

Saving and Loading the Oscilloscope Configuration

.. 10-31

Using the Data Acquisition Blocks in Simulink

Overview ......................................... 11-2

Opening the Data Acquisition Block Library

Using the daqlib Command from the MAT LAB

Workspace

Using the Simulink Library Browser

Building Simulink Models to Acquire Data from a

Device

Data Acquisition Toolbox Block Library Example: Bringing Analog Data into a Model

..................................... 11-4

.................. 11-5

.......................................... 11-7

............... 11-7

......... 11-4

.......... 11-7

Function Reference

Device Object Creation ............................. 12-2

Channels and Lines

Property Getting and Setting

Object Execution

Data Manipulation

................................ 12-3

....................... 12-4

.................................. 12-5

................................. 12-6

xiii

Information and Help .............................. 12-7

Utilities

........................................... 12-8

Functions — Alphabetical List

Base Property Reference

Analog Input Properties ............................ 14-3

Common Properties Channel Properties

Analog Output Properties

Common Properties Channel Properties

Digital I/O Properties

Common Properties Line Properties Getting Command-Line Property Help

................................ 14-3

................................ 14-6

.......................... 14-7

................................ 14-7

................................ 14-10

.............................. 14-11

................................ 14-11

................................... 14-12

................ 14-13

xiv Contents

Base Properties — Alphabetical List

Device-Specific Property by Vendor Reference

Advantech ........................................ 16-2

Measurement Computing

National Instruments

Parallel Port

Sound Card

Getting Command-Line Property Help

Device-Specific Properties — Alphabetical List

...................................... 16-4

....................................... 16-4

........................... 16-2

.............................. 16-2

................ 16-5

Block Reference

Troubleshooting Your Hardware

Advantech Hardware .............................. A-3

What Driver Are You Using?

........................ A-3

Is Your Hardware Functioning Properly? .............. A-3

Measurement Computing Hardware

What Driver Are You Using? Is Your Hardware Functioning Properly?

National Instruments Hardware

NI-DAQmx Versus Traditional NI-DAQ Drivers What Driver Are You Using? Is Your Hardware Functioning Properly?

Sound Cards

Verify If Your Sound Card Is Functioning MicrophoneandSoundCardTypes Testing with a Microphone Testing with a CD Player Running in Full-Duplex Mode

Other M anufactu rers

Other Things to T ry

Registering the Hardware Driver Adaptor Contacting The MathWorks

...................................... A-10

.............................. A-18

................................ A-19

........................ A-5

........................ A-8

.......................... A-15

........................... A-15

....................... A-16

......................... A-20

................. A-5

.................... A-7

................... A-14

.............. A-5

........ A-7

.............. A-9

.............. A-10

............. A-19

xvi Contents

nal Instrumen ts Hardware

Natio

urement Computing Hardwa re

Meas

dows Sound Cards

Win

Vendor Limitations

....................

.................

.............................

B-2

B-4

B-5

Managing Your Memory Resources

Memory Allocation ................................. C-2

How M uch Memory Do You Need?

Example: Managing Memory Resources

Getting Started with Data Acquisition Toolbox

Software

Getting Started with A nalog Input

Doing More with Analog Input

Analog Output

Digital I/O

........................................ D-2

...................... D-2

..................................... D-2

......................................... D-3

................... C-4

............. C-5

Examples

.................. D-2

Saving and Loading the Session

Bringing Analog Data into a Model

..................... D-3

.................. D-3

xvii

Glossary

Index

xviii Contents

Introduction to Data Acquisition

Before you set up any data acquisition system, you should understand the physical quantities you want to measure, the characteristics of those physical quantities, the appropriate sensor to use, and the appropriate data acquisition hardware to use.

The purpose of this chapter is to provide you with some general guidelines about making measurements with a data acquisition system. The information provided should assist you in understanding the above considerations, and understanding the specification sheet associated with your hardware. The sections are as follows.

• “Product Overview” on page 1-2

• “Anatomy of a Data Acquisition Experiment” on page 1-5

• “Data Acquisition System” on page 1-7

• “Analog Input Subsystem” on page 1-20

• “Making Quality Measurements” on page 1-34

• “Getting Command-Line Function Help” on page 1-45

• “Selected Bibliography” on page 1-46

1 Introduction to Data Acquisition

Product Overview

In this section...

“Understanding Data Acquisition Toolbox Software” on page 1-2

“Exploring the Toolbox” on page 1-3

“Supported Hardware” on page 1-4

Understanding Data Acquisition Toolbox Software

Data Acquisition Toolbox™ software is a collection of functions and a MEX-file (shared library) built on the MATLAB The toolbox also includes several dynamic link libraries (DLLs) called adaptors, which enable you to interface with specific hardware. The toolbox provides you with these main features:

• A framework for bringing live, measured data into the M ATL AB workspace

using PC-compatible, plug-in data acquisition hardware

technical computing environment.

1-2

• Support for analog input (AI), analog output (AO), and digital I/O (DIO)

subsystems including simultaneous analog I/O conversions

• Support for these popular hardware vendors/devices:

- Advantech

boards that use the Advantech Device Manager

- Measurement Computing™ Corporation (ComputerBoards) boards

- National Instruments

NI-DAQmx software

Note The Traditional NI-DAQ adaptor will be deprecated in a future version of the toolbox. If you create a Data Acquisition Toolbox™ object for Traditional NI-DAQ adaptor beginning in R2008b, you will receive a warning stating that this adaptor will be removed in a future release. See the supported hardware page at

www.mathworks.com/products/daq/supportedio.html for more

information.

boards that use Traditional NI-DAQ or

- Parallel ports LPT1-LPT3

Note The parallel port adaptor will be deprecated in a future

version of the toolbox. If you create a Data Acquisition Toolbox™ object for receive a warning stating that this adaptor will be removed in a future release. See the supported hardware page at

www.mathworks.com/products/daq/supportedio.html for more

information.

'parallel' beginning in R2008b, you will

Product Overview

- Microsoft

Additionally, you can use the Data Acquisition Toolbox A daptor Kit to interface unsupported hardware devices to the toolbox.

• Event-driven acquisitio ns

Windows®sound cards

Exploring the Toolbox

A list of the toolbox functions is available to you by typing

help daq

You can view the code for any function by typing

type function_name

You can view the help for any function by typing

daqhelp function_name

You can change the way any toolbox function works by copying and renaming the file, then modifying your copy. You can also extend the toolbox by adding your own files, or by using it in combination with other products such as Signal Proce ssing Toolbox™ or Instrument Control T oolbo x™.

The MathWorks™ provides several related products that are especially relevant to the kinds of tasks you can perform with Data Acquisition Toolbox software. For more information about any of these products, see

http://www.mathworks.com/products/daq/related.jsp.

1-3

1 Introduction to Data Acquisition

Supported Hardw

The list of hardw change in each re MathWorks Web s

To see the full hardware page For more infor Hardware” on

are supported by the Data Acquisition Toolbox software can

lease, since hardware support is frequently added. The

ite is the best place to check for the most up-to-date listing.

list of hardware that the toolbox supports, visit the supported

www.mathworks.com/products/daq/supportedio.html.

mation about unsupported hardware, see “Unsupported page 2-11.

are

1-4

Anatomy of a Data Acquisition Experiment

In this section...

“System Setup” on page 1-5

“Calibration” on page 1-5

“Trials” on page 1-6

System Setup

The first step in any data acquisition experiment is to install the hardware and software. Hardware installation consists of plugging a board into your computer or installing modules into an external chassis. Software installation consists of loading hardware drivers and application software onto your computer. After the hardware and software are installed, you can attach your sensors.

Calibration

After the hardware and software are installed and the sensors are connected, the data acquisition hardware should be calibrated. Calibration consists of providing a known input to the system and recording the output. For many data acquisition devices, calibration can be easily accomplished with software provided by the vendor.

1-5

1 Introduction to Data Acquisition

Trials

After the hardwa You might think t signal you are m acquisition sy

re is set up and calibrated, you can begin to acquire data.

hat if you completely understand the characteristics of the

easuring, then you should be able to configure your data

stem and acquire the data.

In the real wor noise levels a higher rate, frequency co

These realmeasuremen different h perform mu

or perhaps you need to add an antialias filter to remove unwanted

mponents.

world effects act as obstacles between you and a precise, accurate

t. To overcome these obstacles, you need to experiment with

ardware and software configurations. In other words, you need to

ltiple data acquisition trials.

ld however, your sensor might be picking up unacceptable

nd require shielding, o r you might need to run the device at a

1-6

Data Acquisition System

In this section...

“Overview” on page 1-7

“Data Acquisition Hardware” on page 1-10

“Sensors” on page 1-11

“Signal Conditioning” on page 1-15

“The Computer” on page 1-17

“Software” on page 1-17

Overview

The Data Acquisition Toolbox software, in conjunction with the MA TLAB technical computing environment, gives you the ability to measure and analyze physical phenomena. The purpose of any data acquisition system is to provide you with the tools and resources necessary to do so .

Data Acquisition System

You can think of a data acquisition system as a collection of software and hardware that connects you to the physical w orld . A typical data acquisition system consists of these components.

Components

Data acquisition hardware

sors and

Sen

uators

act

ransducers)

iption

Descr

e heart of any data acquisition system lies the

At th

acquisition hardware. Th e main function of this

data

ware is to convert analog signals to digital s ignals,

hard

o conve rt digital signals to analog signals.

and t

sors and actuators can both be transducers.A

Sen

nsducer is a device that converts input energy of one

tra

rm into output energy of another form. For example,

icrophone is a sensor that converts sound energy

n the form of pressure) into electrical energy, while

oudspeaker is an actuator that converts electrical

nergy into sound energy.

1-7

1 Introduction to Data Acquisition

Components

Signal conditioning hardware

Computer

Software Data acquisition software allows you to exchange

The data acquisition components, and their relationship to each other, are shown below.

Description

Sensor signals are often incompatible w ith data acquisition hardware. To overcome this incompatibility, the signal must be conditioned. For example, you might need to condition an input signal by amplifying it or by removing unwanted frequency components. Output signals might need conditioning as well. However, only input signal conditioning is discussed in this chapter.

The computer provides a proces sor, a system clock, a bus to transfer data, and memory and disk space to store data.

information between the computer and the hardware. For example, typica l software allows y o u to configure the sampling rate of your board, and acquire a predefined amount of data.

1-8

Data Acquisition System

The figure depicts the two important features of a data acquis ition system :

• Signals are input to a sensor, conditioned, converted into bits that a

computer can read, and analyzed to extract meaningful information.

For example, sound level data is acquired from a microphone, amplified, digitized by a sound card, and stored in MATLAB workspace for subsequent analysis of frequency content.

• Data from a computer is converted into an analog signal and output to

an actuator.

For example, a vector of data in MATLAB workspace is converted to an analog signal by a sound card and output to a loudspeaker.

1-9

1 Introduction to Data Acquisition

Data Acquisitio

Data acquisitio expansion slot i computer throu

At the simples subsystems it hardware that

• Analog input

• Analog outp

• Digital inp

• Counter/ti

Hardware d depicted b

n hardware is either internal and installed directly into an

nside your computer, or external and connected to your

gh an external cable, which is typically a USB cable.

t level, data acquisition hardware is characterized by the

possesses. A subsystem is a component of your data acquis ition

performs a specialized task. Common subsystems include

ut/output

mer

evices that consist of multiple subsystems, such as the one

elow, are called multifunction boards.

n Hardware

1-10

Analog Input Subsystems

Analog input subsystems convert real-world analog input signals from a sensor into bits that can be read by your computer. Perhaps the most important of all the subsystems commonlyavailable,theyaretypically multichannel devices offering 12 or 16 bits of resolution.

Analog input subsystems are also referred to as AI subsystems, A/D converters, or ADCs. Analog input subsystems are discussed in detail beginning in “Analog Input Subsystem” on page 1-20.

Data Acquisition System

Analog Output Subsystems

Analog output subsystems convert digital data store d on your computer to a real-world analog signal. These subsystems perform the inverse conversion of analog input subsystems. Typical acquisition boards offer two output channels wi th 12 bits of resolution, with special hardware availabletosupport multiple channel analog output operations.

Analog output subsystems are also referred to as AO subsystems, D/A converters, or DACs.

Digital Input/Output Subsystems

Digital input/output (DIO) subsystems are designed to input and output digital values (logic levels) to and from hardware. These values are typically handled either as single bits or lines,orasaport, which typically consists of eight lines.

While most popular data acquisition cards in clude some dig ita l I/O ca pa b il ity , it is usually limited to simple operations, and special dedicated hardware is often necessary for performing advanced digital I/O operations.

Counter/Timer Subsystems

Counter/timer (C/T) subsystems are used for event counting, frequency and period measurement, and pulse train generation.

Sensors

A sensor converts the physical pheno m ena of interest into a signal that is input into your data acquisition hardware. There are two main types of sensors based on the output they produce: digital sensors and analog sensors.

Digital sensors produce an output signal that is a digital representation of the input signal, and has discrete values of magnitude measured at discrete times. A digital se ns or must output logic levels that are compatible with the digital receiver. Some standard logic levels include transistor-transistor logic (TTL) and emitter-coupled logic (ECL). Examples of digital sensors include switches and p osition encoders.

1-11

1 Introduction to Data Acquisition

Analog sensors produce an output signal that is directly proportional to the input signal, and is continuous in both magnitude and in time. Most physical variables such as temperature, pressure, and acceleration are continuous in nature and are readily m easured withananalogsensor. Forexample,the temperature of an automobile cooling system and the acceleration produced by a child on a swing all vary continuously.

The sensor you use depends on the phenomena you are measuring. Some common analog sensors and the physical variables they measure are listed below.

Common Analog Sensors

Sensor Physical Variable

Accelerometer Acceleration

Microphone

Pressure gauge Pressure

Resistive temperature device (RTD)

Strain gauge

Thermocouple

When choosing the best analog sensor to use, you must match the characteristics of the physical variable you are measuring with the characteristics of the sensor. The two most important senso r characteristics are:

• The sensor output

• The sensor bandwidth

Pressure

Temperature

Force

Temperature

Sensor Output

The output from a sensor can be an analog signal or a digital signal, and the output variable is usually a voltage although some sensors output current.

1-12

Data Acquisition System

Current Signals. Current is often used to transmit signals in noisy environments because it is much less affected by environmental noise. The full scale range of the current signal is often either 4-20 mA or 0-20 mA. A 4-20 mA signal has the advantage that even at minimum signal value, there should be a detectable current flowing. The absence of this indicates a wiring problem.

Before conversion by the analog input subsystem, the current signals are usually turned into voltage signals by a current-sensing resistor. The resistor should be of high precision, perhaps 0.03% or 0.01% depending on the resolution of your hardware. A dditionally, the voltage signal should match the signal to an input range of the analog input hardware. For 4-20 mA signals, a 50 ohm resistor will give a voltage of 1 V for a 20 mA signal by Ohm’s law.

Voltage Signals. The most commonly interfaced signal is a voltage signal. For example, thermocouples, strain gauges, and accelerometers all produce voltage signals. There are three major aspects of a voltage signal that you need to consider:

• Amplitude

If the signal is smaller than a few millivolts, you might need to amplify it. If it is larger than the maximum range of your analog input hardware (typically ±10 V), you will have to divide the signal down us i ng a resistor network.

The amplitude is related to the sensitivity (resolutio n) of your hardware. Refer to “Accuracy and Precision” on page 1-34 for more information about hardware sensitivity.

• Frequency

Whenever you acquire data, you should decide the highest frequency you want to measure.

The highest frequency component of the signal determines how often you should sample the input. If you have more than one input, but only one analog input subsystem, then the overall sampling rate goes up in proportion to the number of inputs. Higher frequencies might be present as noise, which you can remove by filtering the signal before it is digitized.

If you sample the input signal at least twice as fast as the highest frequency component, then that signal will be uniquely characterized. However, this

1-13

1 Introduction to Data Acquisition

rate might not mimic the waveform very closely. For a rapidly varying signal, you might need a sampling rate of roughly 10 to 20 times the highest frequency to get an accurate picture of the waveform. For slowly varying signals, you need only consider the minimum time for a significant change in the signal.

The frequency is related to the bandwidth of your measurement. Bandwidth is discussed in the next section.

• Duration

How long do you want to sample the signal for? If you are storing data to memory or to a disk file, then the duration determines the storage resources required. The format of the stored data also affects the amount of storage space required. For example, data stored in ASCII format takes more space than data stored in binary format.

Sensor Bandwidth

Inareal-worlddataacquisitionexperiment, the physical phenomena you are measuring has expected limits. For example, the tempera ture of your automobile’s cooling system varies continuously betwee n its low limit and high limit. The temperature limits, as w ell as how rapidly the temperature varies between the limits, depends on several factors including your driving habits, the weather, and the condition of the cooling system. The expected limits might be readily approximated, but there are an infinite number of possible temperatures that you can measure at a given time. As explained in “Quantization” on page 1-24, these unlimited possibilities are mapped to a finite set of values by your data acquisition hardware.

1-14

The bandwidth is given by the range of frequencies present in the signal being measured. You can also think of bandwidth as being related to the rate of change of the signal. A slowly varying signal has a low bandwidth, while a rapidly varying signal has a high bandwidth. To properly measure the physical phenomena of interest, the sensor bandwidth must be compatible with the measurement bandwidth.

You might want to use sensors with the widest possible bandwidth when making any physical measurement. This is the one way to ensure that the basic measurement system is capable of responding linearly over the full range of interest. However, the wider the bandwidth of the sensor, the

Data Acquisition System

more you must be concerned with eliminating sensor response to unwanted frequency components.

Signal Conditioning

Sensor signals are often incompatible with data acquisition hardware. To overcome this in compatibility, the sensor signal must be conditioned. The type of signal conditioning required depends on the sensor you are using. For example, a signal might have a small amplitude and require amplification, or it might contain unwanted frequency components and require filtering. Common ways to condition signals include

• Amplification

• Filtering

• Electrical isolation

• Multiplexing

• Excitation source

Amplification

Low-level – less than around 100 millivolts – usually need to be amplified. High-level signals might also require amplification depending on the input range of the analog input subsystem.

For example, the output signal from a thermocouple is small and must be amplified before it is digitized. Signalamplificationallowsyoutoreduce noise and to make use of the full range of your hardware thereby increasing the resolution of the measurement.

Filtering

Filtering removes unwanted noise from the signal of interest. A noise filter is used on slowly varying signals such as temperature to attenuate higher frequency signals that can reduce the accuracy of your measurement.

Rapidly varying signals such as vibration often require a different type of filter known as an antialiasing filter. An antialiasing filter removes undesirable higher frequencies that might lead to erroneous measurements.

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1 Introduction to Data Acquisition

Electrical Isolation

If the signal of interest contains high-voltage transients that could damage the computer, then the sensor signals should be electrically isolated from the computer for safety purposes.

You can also use electrical isolation to make sure that the readings from the data acquisition hardware are not affected by differences in ground potentials. For example, when the hardware device and the sensor signal are each referenced to ground, problems occur if there is a potential difference between the two grounds. This difference can lead to a ground loop,which might lead to erroneous measurements. Using electrically isolated signal conditioning modules eliminates the ground loop and ensures that the signals are accurately represented.

Multiplexing

A common technique for measuring several signals with a single measuring device is multiplexing.

1-16

Signal conditioning devices for analog signals often provide multiplexing for use w ith slowly changing signals such as temperature. This is in addition to any built-in multiplexing on the DAQ board. The A/D converter samples one channel, switches to the next channel and samples it, switches to the next channel, and so on. Because the same A/D converter is sampling many channels, the effective sampling rate of each individual channel is inversely proportional to the number of channels sampled.

You must take care when using multiplexers so that the switched signal has sufficient time to settle. R efer to “Noise” on page 1-38 for more information about settling time.

Excitation Source

Some sensors require an excitation source to operate. For example, strain gauges, and resistive temperature devices (RTDs) require external voltage or current excitation. Signal conditioning modules for these sensors usually provide the necessary excitation. RTD measurements are usually made with a current source that converts the variation in resistance to a measurable voltage.

The Computer

The computer pro memory and disk s

vides a processor, a system clock, a bus to transfer data, and

Data Acquisition System

pace to store data.

The processor c clock provide recorded a sen when that meas

Data is trans memory acces therefore e between whe responds. T bus archit for more in

s time information about the acquired data. Knowing that you

ferred from the hardware to system memory via dynamic

s (DMA) or interrupts. DMA is hardware controlled and

xtremely fast. Interrupts might be slow because of the latency time

n a board requests interrupt servicing and when the computer

he maximum acquisition rate is also determined by the computer’s

ecture. Refer to “How Are Acquired Samples Clocked?” on page 1-27

formation about DMA and interrupts.

Software

Regardle to the ha configu receive error me so that This in

There

ss of the hardware you are using, you must send information rdware and receive information from the hardware. You send

ration information to the hardware such as the sampling rate, and

information from the hardware s uch as data, status messages, and

ssages. You might also need to supply the hardware with information

you can integrate it with other hardware and with computer resources.

formation exchange is accomplished with software.

are two kinds of software:

ontrols how fast data is accepte d by the converter. The system

sor reading is generally not enough. You also need to know

urement occurred.

• Drive

• Appl

rsoftware

ication software

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1 Introduction to Data Acquisition

For example, suppose you are using Data Acquisition Toolbox software with a National Instruments AT-MIO-16E-1 board and its associated NI-DAQ driver. The relationship between you, the driver so ftware, the application software, and the hardware is shown below.

1-18

The diagram illustrates that you supply information to the hardware, and you receive information from the hardware.

Driver

For data acquisition device, there is associated driver software that you must use. Driver software allows you to access and control the capabilities of your hardware. Among other things, basic driver software allows you to

• Bring data on to and get data off of the board

• Control the rate at which data is acquired

• Integrate the d a ta acquisition hardware with computer resources such as

• Integrate the data acquisition hardware with signa l conditioning hardware

• Access multiple subsystems on a given data acquisition board

• Access multiple data acquisition boards

Software

processor interrupts, DMA, and memory

Data Acquisition System

Application Software

Application software provides a convenient front end to the driver software. Basic application software allows you to

• Report relevant information such as the number of samples acquired

• Generate events

• Manage the data stored in computer memory

• Condition a signal

• Plot acquired data

With some application software, you can also perform analysis on the data. MATLAB and Data Acquisition Toolbox software provide you with these capabilities and more.

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1 Introduction to Data Acquisition

Analog Input Subsystem

In this section...

“Function of the Analog Input Subsystem” on page 1-20

“Sampling” on page 1-20

“Quantization” on page 1-24

“Channel Configuration” on page 1-28

“Transferring Data from Hardware to System Memory” on page 1-31

Function of the Analog Input Subsystem

Many data acquisition hardware devices contain one or more subsystems that convert (digitize) real-world sensor signals into numbers your computer can read. Such devices are called analog input subsystems (AI subsystems, A/D converters, or ADCs). A fter the r ea l- world sig nal is digitized, you can analyze it, store it in system memory, or store it to a disk file.

1-20

The function of the analog input subsystem is to sample and quantize the analog signal using one or more channels. You can think of a channel as a path through which the sensor signal travels. Typical analog input subsystems have eight or 16 input channels available to you. After data is sampled and quantized, it must be transferred to system memory.

Analog signals are continuous in time and in amplitude (within predefined limits). Sampling takes a “snapshot” of the signal at discrete times, while quantization divides the voltage (or current) value into discrete amplitudes. Sampling, quantization, channel configuration, and transferring data from hardware to system memory are discussed next.

Sampling

Sampling takes a snapshot of the sensor signal at discrete times. For most applications, the time interval between samples is kept constant (for example, sample every millisecond) unless externally clocked.

For most dig ital converters, sampling is performed by a sample and hold (S/H) circuit. An S/H circuit usually consists of a signal buffer followed by an

Analog Input Subsystem

electronic switch connected to a capacitor. The operation of an S/H circuit follows these steps:

1 At a given sampling instant, the switch connects the buffer and capacitor

to an input.

2 The capacitor is charged to the input voltage.

3 The charge is held until the A/D converter digitizes the signal.

4 For multiple channels connected (multiplexed) to o ne A/D converter, the

previous s teps are repeated for each input channel.

5 The entire process is repeated for the next sampling instant.

A multiplexer, S/H circuit, and A/D converter are illustrated in the next section.

Hardware can be divided into two main categories based on how signals are sampled: scanning hardware, which samples input signals sequentially, and simultaneous sample and hold (SS/H) hardware, which samples all signals at thesametime. Thesetwotypesofhardwarearediscussedbelow.

Scanning Hardware

Scanning hardware samples a single input signal, converts that signal to a digital value, and then repeats the process for every input channel used. In other words, each input channel is sampled sequentially. A scan occurs when each input in a group is sampled once.

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1 Introduction to Data Acquisition

As show n below, mos t data acquisition devices have one A/D converter that is multiplexed to multiple input channels.

Therefore, simultaneo This time g as the time

Addition applies f is given b

if you use multiple channels, those channels cannot be sampled uslyandatimegapexistsbetweenconsecutive sampled channels.

ap is called the channel skew. You can think of the channel skew

it takes the analog input subsystem to sample a single channel.

ally, the maximum sampling rate your hardware is rated at typically or one channel. Therefore, the maximum sampling rate per channel

y the formula:

maximum sampling rate per channel

maximum board rate

eer of channels scanned

numb

1-22

Analog Input Subsystem

Typically, you can achieve this maximum rate only under ideal conditions. In practice, the sampling rate depends on several characteristics of the analog input subsystem including the settling time and the gain, as well as the channel skew. The sample period and channel skew for a multichannel configuration using scanning hardware is shown below.

If you cannot tolerate channel skew inyourapplication, you must use hardware that allows simultaneous sampling of all channels. Simultaneous sample and hold hardware is discussed in the next section.

Simultaneous Sample and Hold Hardware

Simultaneous sample and h old (SS/H) hardware samples all input signals at the same time and holds the values until the A/D converter digitizes all the signals. For high-end systems, there can be a separate A/D converter for each input channel.

For example, suppose you need to simultaneously measure the acceleration of multiple accelerometers to determine the vibration of some device under test. To do this, you must use SS/H hardware because it does not have a channel skew. In general, you might need to use SS/H hardware if your sensor signal changes significantly in a time that is less than the channel skew, or if you need to use a transfer function or perform a frequency domain correlation.

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1 Introduction to Data Acquisition

The sample period for a multichannel configuration using SS/H hardware is shown below. Note that there is no channel skew.

Quantization

As discussed in the previous section, sampling takes a snapshot of the input signal at an instant of time. When the snapshot is taken, the sampled analog signal must be converted from a voltage value to a binary number that the computer can read. The conversion from an infinitely precise amplitude to a binary number is called quantization.

1-24

During quantization, the A/D converter uses a finite number of evenly spaced values to represent the analog signal. The number of different values is determined by the number of bits used for the conversion. Most modern converters use 12 or 16 bits. Typically, the converter selects the digital value that is closest to the actual sampled value.

Analog Input Subsystem

The fig ure below shows a 1 Hz sine wave quantized by a 3 bit A/D converter.

The number of quantized values is given by 23= 8, the largest representable value is given by 111 = 2

2+21+20

= 7.0, and the smallest representable

value is given by 000 = 0.0.

Quantization Error

There is always some error associated with the quantization of a continuous signal. Ideally, the maximum quantization error is ±0.5 least significant bits (LSBs), and over the full input range, the average quantization error is zero.

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1 Introduction to Data Acquisition

As shown below, the quantization error for the previous sine wave is calculated by subtracting the actual signal from the quantized signal.

1-26

Input Range and Polarity

The input range of the analog input subsystem is the span of input values for which a conversion is valid. You can change the input range by selecting a different gain value. For example, National Instruments’ AT-MIO-16E-1 board has eight gain values ranging from 0.5 to 100. Many boards include a programmable gain amplifier that allows you to change the device gain through software.

When an input signal exceeds the valid input range of the converter, an overrange condition occurs. In this case, most devices saturate to the largest representable value, and the converted data is almost definitely incorrect. The gain setting affects the precision of your measurement — the higher (lower) the gain value, the lower (higher) the precision. Refer to “How Are Range, Gain, and Measurement Precision Related?” on page 1-37 for more information about how input range, gain, and precision are related to each other.

Analog Input Subsystem

An analog input subsystem can typically convert both unipolar signals and bipolar signals. A unipolar signal contains only positive values and zero,

while a bipolar signal contains positive values, negative values, and zero.

Unipolar and bipolar signals are depicted below. Refer to the figure in “Quantization” on page 1-24 for an example of a unipolar signal.

In many cases, the signal polarity is a fixed characteristic of the sensor and you must configure the input range to match this polarity.

As you can see, it is crucial to understand the range of signals expected from your sensor so that you can configure the input range of the analog input subsystemtomaximizeresolutionandminimizethechanceofanoverrange condition.

How Are Acquired Samples Clocked?

Samples are acquired from an analog input subsystem at a specific rate by a clock. Like any timing system, data acquisition clocks are characterized their resolution and accuracy. Timing resolution is defined as the smallest time interval that you can accurately measure. T he timing accuracy is affected by clock jitter. Jitter arises when a clock produces slightly different values for a given time interval.

For a ny data acquisition system, there are typically three clock sources that you can use: the onboard data acquisition clock, the computer clock, or an

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1 Introduction to Data Acquisition

external clock. Data Acquisition Toolbox software supports all of these clock sources, depending on the requirements of your hardware.

Onboard Clock. The onboard clock is typically a timer chip on the hardware board that is programmed to generate a pulse stream at the desired rate. The onboard clock generally has high accuracy and low jitter compared to the computer clock. You should always use the onboard clock when the sampling rate is high, and when you require a fixed time interval between samples. The onboard clock is referred to as the internal clock in this guide.

Computer Clock. The computer (PC) clock is used for boards that do not possess an onboard clock. The computer clock is less accurate and has more jitter than the onboard clock, and is generally limited to sampling rates below 500 Hz. The computer clock is referred to as the software clock in this guide.

External Clock. An external clock is often used when the sampling rate is low a nd not constant. For example, an external clock source is often used in automotive applications where samples are acquired as a function of crank angle.

1-28

Channel Configuration

You can configure input channels in one of these two ways:

• Differential

• Single-ended

Your choice of input channel configuration might depend on whether the input signal is floating or grounded.

A floating signal uses a n isolated ground reference and is not connected to the building ground. A s a result, the input signal and hardware device are not connected to a common reference, which can caus e the input signal to exceed the valid range of the hardware device. To circumvent this problem, you must connect the signal to the onboard ground of the device. Examples of floating signal sources include ungrounded thermocouples and battery devices.

A grounded signal is connected to the building ground. As a result, the input signal and hardware device are connected to a comm on reference. Examples of

Analog Input Subsystem

grounded signal sources include nonisolated instrument outputs and devices that are connected to the building power system.

Note For more information about channel configuration, refer to your hardware documentation.

Differential Inputs

When you configure your hardware for differential input, there are two signal wires associated with each input signal — one for the input signal and one for the reference (return) signal. T he measurement is the difference in voltage between the two wires, which helps reduce noise and any voltage that is common to both wires.

As shown below, the input signal is connected to the positive amplifier socket (labeled +) and the return signal is connected to the negative amplifier socket (labeled -). The amplifier has a third connector tha t allows these signals to be referenced to ground.

National Instruments recommends that you use differential inputs under any of these conditions:

• The input signal is low level (less than 1 volt).

• The leads connecting the signal are greater than 10 feet.

• The input signal requires a separate ground-reference point or return

signal.

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1 Introduction to Data Acquisition

• The signal leads travel through a noisy environment.

Single-Ended Inputs

When you configure your hardware for single-ended input, there is one signal wire associated with each input signal, and each input signal is connected to the same ground. Single-ended measurements are more susceptible to noise than differential measurements because of differences in the signal paths.

As shown below, the input signal is connected to the positive amplifier socket (labeled +) and the ground is connected to the negative amplifier socket (labeled -).

1-30

National Instruments suggests that you can use single-ended inputs under any of these conditions:

• The input signal is high level (greater than 1 volt).

• The leads connecting the signal are less than 10 feet.

• The input signal can share a common reference point with other signals.

You should use differential input connectors for any input signal that do es not meet the preceding conditions. You can configure many National Instruments boards for two different types of single-ended connections:

• Referenced single-ended (RSE) connection

The R SE configuration is used for floating signal sources. In this case, the hardware device itself provides the reference ground for the input signal.

Analog Input Subsystem

• Nonreferenced single-ended (NRSE) connection

The NRSE input configuration is used for grounded signal sources. In this case, the input signal provides its own reference ground and the hardware device should not supply one.

Refer to your National Instruments hardware documentation for more information about RSE and NRSE connections.

Transferring Data from Hardware to System Memory

The transfer of acquired data from the hardware to system memory follows these steps:

1 Acquired data is stored in the hardware’s first-in first-out (FIFO) buffer.

2 Data is transferred from the FIFO buffer to system memory using

interrupts or DMA.

These steps happen automatically. Typically, all that’s required from you is some initial configuration of the ha r dwaredevicewhenitisinstalled.

FIFO Buffer

The FIFO buffer is used to temporarily store acquired data. The data is temporarily stored until it can be transferred to system memory. The p rocess of transferring data into and out of an an a lo g input F IFO buffer is given below:

1 The FIFO buffer stores newly acquired samples at a constant sampling rate.

2 Before the FIFO buffer is filled, the software starts removing the samples.

For example, an interrupt is generated when the FIFO is half full, and signals the software to extract the samples as quickly as possible.

3 Because servicing interrupts or programming the DMA controller can take

up to a few milliseconds, additional data is stored in the FIFO for future retrieval. For a larger FIFO buffer, longer latencies can be tolerated.

4 Thesamplesaretransferredtosystemmemoryviathesystembus(for

example, PCI bus or AT bus). After the samples are transferred, the software is free to perform other tasks until the next interrupt occurs. For

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1 Introduction to Data Acquisition

example, the data can be processed or saved to a disk file. As long as the average rates of storing and extracting data are equal, acquired data will not be missed and your application should run smoothly.

Interrupts

The slowest but most common method to move acquired data to system memory is for the board to generate an interrupt request (IRQ) signal. This signal can be generated when one sample is acquired or when multiple samples are acquired. The process of transferring data to system memory viainterruptsisgivenbelow:

1 When data is ready for transfer, the CPU stops whatever it is doing and

runs a special interrupt handler routine that saves the current machine registers, and then sets them to access the board.

2 The data is extracted from the board and placed into system memory.

3 The saved machine registers are restored, and the CPU returns to the

original interrupted process.

1-32

The actual d ata move is fairly quick, but there is a lot of overhead time spent saving, setting up, and restoring the register information. Therefore, depending on your specific system, transferring data by interrupts might not be a good choice when the sampling rate is greater than around 5 kHz.

DMA

Direct memory access (D MA ) is a system whereby samples are automatically stored in system memo ry while the processor does something else. The process of transferring data via DMA is given below:

1 When data is ready for transfer, the board directs the system DMA

controller to put it into in system memory as soon as possible.

2 As soon as the CPU is able (which is usually very quickly), it stops

interacting with the data acquisition hardware and the DMA controller moves the data directly into memory.

3 TheDMAcontrollergetsreadyforthenextsamplebypointingtothenext

open memory location.

Analog Input Subsystem

4 The previous steps are repeated indefinitely, with data going to each open

memory location in a continuously circulating buffer. No interaction between the CPU and the board is needed.

Your computer supports several different DMA channels. Depending on your application, you can use one or more of these channels, For example, simultaneous input and output with a sound card requires one DMA channel for the input and another DMA channel for the output.

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1 Introduction to Data Acquisition

Making Quality M easurements

In this section...

“What Do You Measure?” on page 1-34

“Accuracy and Precision” on page 1-34

“Noise” on page 1-38

“Matching the Sensor Range and A/D Converter Range” on page 1-40

“How Fast Should a Signal Be Sampled?” on page 1-40

What Do You Measure?

For most data acquisition applications , you need to measure the signal produced by a sensor at a specific rate.

In many cases, the sensor signal is a voltage level that is proportional to the physical phenomena of interest (for example, temperature, pressure, or acceleration). If you are measuringslowlychanging(quasi-static) phenomena like temperature, a slow sampling rate usually suffices. If you are measuring rapidly changing (dynamic) phenomena like vibration or acoustic measurements, a fast sampling rate is required.

1-34

To make high-quality measurements, you should follow these rules:

• Maximize the precision and accuracy

• Minimize the noise

• Match the sensor range to the A/D range

Accuracy and Precision

Whenever you acquire measured data, you should make every effort to maximize its accuracy and precision. The quality of your measurement depends on the accuracy and precision of the entire data acquisition system, and can be limited by such factors as board resolution or environmental noise.

In general terms, the accuracy of a measurement determines how close the measurement comes to the true v alue. Therefore, it indicates the correctness

Making Quality Measurements

of the result. The precision of a measurement reflects how exactly the result is determined without reference to what the result means. The relative precision indicates the uncertainty in a measurement as a fraction of the result.

For example, suppose you measure a table top with a meter stick and find its length to be 1.502 meters. This number indicates that the meter stick (and your eyes) can resolve distances down to at least a millimeter. Under most circumstances, this is consideredtobeafairlyprecisemeasurement with a relative precision of around 1/1500. However, suppose you perform the measurement again and obtain a result of 1.510 meters. After careful consideration, you discover t h at your initial technique for reading the meter stick was faulty because you did not read it from directly above. The refore, the first measurement was not accurate.

Precision and accuracy are illustrated below .

For analog input subsystems, accuracy is usually limited by calibration errors while precision is usually limited by the A/D converter. Accuracy and precision are discussed in more d etail below.

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1 Introduction to Data Acquisition

Accuracy

Accuracy is defined as the agreement between a measured quantity and the true value of that quantity. Every component that appears in the analog signal path affects system accuracy and performance. The overall system accuracy is given by the component with the worst accuracy.

For data acquisition hardware, accuracy is often expressed as a percent or a fraction of the least significant bit (L SB). Under ideal circumstances, board accuracy is typically ±0.5 LSB. Therefore, a 12 bit converter has only 11 usable bits.

Many boards include a programmable gain a mplifier, which is located just before the converter input. To prevent system accuracy from being degraded, the accuracy and linearity of the gain must be better than that of the A/D converter. The specified accuracy of a board is also affected by the sampling rate and the settling time of the amplifier. The settling time is defined as the time required for the instrumentationamplifiertosettletoaspecified accuracy. To maintain full accuracy, the amplifier output must settle to a level give n by the magnitude of 0.5 LSB before the next conversion, and is on the order of several tenths of a millisecond for most boards.

1-36

Settling time is a function of sampling rate and gain value. High rate, high gain configurations require longer settling times while low rate, low gain configurations require shorter settling times.

Precision

The number of bits used to represent an analog signal determines the precision (resolution) of the device. The more bits provided by your board, the more precise your measurement will be. A high precision, high resolution device divides the input range into more divisions thereby allowing a smaller detectable voltage value. A low precision, low resolution device divides the input range into fewer divisions thereby increasing the detectable vol t age value.

The overall precision of your data acquisition system is usually determined by the A/D converter, and is specified by the number of bits used to represent the analog signal. Most boards use 12 or 16 bits. The precision of your measurement is given by:

Making Quality Measurements

precision

= one part in 2

number of bits

The precision in volts is given by:

precision

voltage range

number of bits

For example, if you are using a 12 bit A/D converter configured for a 10 volt range, then

volts

precision

This means that the converter can detect voltage differences at the level of

0.00244 volts (2.44 mV).

How Are Range, Gain, and Measurement Precision Related?

When you configure the input range and gain of your analog input subsystem, the end result should maximize the measurement resolution and m inimize the chance of an overrange condition. The actual input range is given by the formula:

actual input range

input range

gain

The relationship between gain, actual input range, and precision for a unipolar and bipolar signal having an input range of 10 V is shown below.

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1 Introduction to Data Acquisition

Relationship Between Input Range, Gain, and Precision

Actual Input

Input Range Gain

0to10V

-5 to 5 V

As shown in the table, the gain affects the precision of your measurement. If yo u select a gain that decreases the actual input range, then the precision increases. Conversely, if you select a gain that increases the actual input range, then the precision decreases. This is because the actual input range varies but the number of bits used by the A/D converter remains fixed.

Note With the Data A cquisition Toolbox s oftware, you do not have to specify the range and gain. Instead, you simply specify the actual input range desired.

1.0

2.0

5.0

10.0

0.5

1.0

2.0

5.0

10.0

Range

0to10V 2.44mV

0to5V 1.22mV

0to2V 0.488mV

0to1V 0.244mV

-10 to 10 V 4.88 mV

-5 to 5 V 2.44 mV

-2.5 to 2.5 V 1.22 mV

-1.0 to 1.0 V 0.488 mV

-0.5 to 0.5 V 0.244 mV

Precision (12 Bit A/D)

1-38

Noise

Noise is considered to be any measurement that is not part of the phenomena of interest. Noise can be generated within the electrical com ponents of the input amplifier (internal noise), or it can be added to the signal as it travels down the input wires to the amplifier (external noise). Techniques that you can use to reduce the effects of noise are described below.

Making Quality Measurements

Removing Internal Noise

Internal noise arises from thermal effects in the amplifier. Amplifiers typically generate a few microvolts of internal noise, which limits the resolution of the signal to this level. The amount of noise added to the signal depends on the bandwidth of the input amplifier.

To reduce internal noise, you should select an amplifier with a bandwidth that closely matches the bandwidth of the input signal.

Removing External Noise

External noise arises from many sources. For example, many data acquisition experiments are subject to 60 Hz noise generated by AC power circuits. This type of noise is referred to as pick-up or hum, and appears as a sinusoidal interference signal in the measurement circuit. Another common interference source is fluorescent lighting. These lightsgenerateanarcattwicethepower line frequency (120 Hz).

Noise is added to the acquisition circuit from these external sources because the signal leads act as aerials picking up environmental electrical activity. Much of this noise is common to both signal wires. To remove m ost of this common-mode voltage, you should

• Configure the input channels in differential mode. Refer to “Channel

Configuration” on page 1-28 for more information about channel configuration.

• Use signal wires that are twisted together rather than separate.

• Keep the signal wires as short as possible.

• Keep the signal wires as far away as possible from environmental electrical

activity.

Filtering

Filtering also reduces signal noise . For many data acquisition applications, a low-pass filter is beneficial. As the name suggests, a low-pass filter passes the lower frequency components but attenuates the higher frequency components. The cut-off frequency of the filter must be compatible with the frequencies present in the signal of interest and the sampling rate used for the A/D conversion.

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1 Introduction to Data Acquisition

A low-pass filter that’s used to prevent higher frequencies from introducing distortion into the digitized signal is known a s an antialiasing filter if the cut-off occurs at the Nyquist frequency. That is, the filter removes frequencies greater than one-ha l f the sampling frequency. These filters generally have a sharper cut-off than the normal low-pass filter used to condition a signal. Antialiasing filters are specified according to the sampling rate of the system and there must be one filter per input signal.

Matching the Sensor Range and A/D Converter Range

When sensor data is digitized by an A/D converter, you must be aware of these two issues:

• The expected range of the data produced by your sensor. This range

depends on the physical phenomena you are measuring and the output range of the sensor.

• The range of your A/D converter. For many devices, the hardware range is

specified by the gain and polarity.

1-40

You should select the sensor and hardware ranges such that the maximum precision is obtained, and the full dynamic range of the input signal is covered.

For example, suppose you are using a microphone with a dynamic range of 20 dB to 140 dB and an output sensitivity of 50 mV/Pa. If you are measuring street noise in your application, then you might expect that the sound level never exceeds 80 dB, which corresponds to a sound pressure magnitude of 200 mPa and a voltage output from the microphone of 10 mV. Under these conditions, you should set the input range of your data acquisition card for a maximum signal amplitude of 10 mV, or a little more.

How F ast Should a Signal Be Sampled?

Whenever a continuous signal is sampled, some information is lost. The key objective is to sample at a rate such that the signal of interest is well characterized and the amount of information lost is minimized.

If you sample at a rate that is too slow, then signal aliasing can o ccur. Aliasing can occur for both rapidly varying signals and slowly varying signals.

Making Quality Measurements

For example, suppose you are measuring temperature once a minute. If your acquisition system is picking up a 60-Hz hum from an AC power supply, then that hum will appear as constant noise level i f you are sampling at 30 Hz.

Aliasing occurs when the sampled signal contains frequency components greater than one-half the sampling rate. The frequency components could originate from the signal of interest in which case you are undersampling and should increase the sampling rate. The frequency components could also originate from noise in which case you might need to condition the signal using a filter. The rule used to prevent aliasing is given by the Nyquist theorem,whichstatesthat

• An analog signal can be uniquely reconstructed, without error, from

samples taken at equal time intervals.

• Thesamplingratemustbeequaltoorgreaterthantwicethehighest

frequency component in the analog signal. A frequency of one-half the sampling rate is called the Nyquist frequency.

However, if your input signal is corrupted by noise, then aliasing can still occur.

1-41

1 Introduction to Data Acquisition

For example, suppose you configure your A/D converter to sample at a rate of 4 samples per second (4 S/s or 4 Hz), and the signal of interest is a 1 Hz sine wave. Because the signal frequency is one-fourth the sampling rate, then according to the Nyquist theorem, it should be completely characterized. However,ifa5Hzsinewaveisalsopresent,thenthesetwosignalscannot be distinguished. In other words, the 1 Hz sine wave produces the same samples as the 5 Hz sine wave when the sampling rate is 4 S/s. This situation is shown below.

1-42

In a re signa

Even of on with

al-world data acquisition environment, you might need to condition the

l by filtering out the high frequency components.

though the samples appear to represent a sine wave with a frequency

e-fourth the sampling rate, the actual signal could be any sine wave

a frequency of:

n sampling rate±

()

025.

()

Making Quality Measurements

where n is zero or any positive integer. For this example, the actual signal could be at a frequency of 3 Hz, 5 Hz, 7 Hz, 9 Hz, and so on. The relationship

0.25

x (Sampling rate) is called the alias of a signal that may be at another

frequency. In other words, aliasing occurs when one frequency assumes the identity of another frequency.

If you sample the input signal at least twice as fast as the highest frequency component, then that signal might be uniquely characterized, but this rate would not mimic the waveform very closely. As shown below, to get an accurate picture of the waveform, you need a sampling rate of roughly 10 to 20 times the highest frequency.

As shown in the top figure, the low sampling rate produces a sampled signal that appears to be a triangular waveform. As shown in the bottom figure, a higher fidelity sampled signal is produced when the sampling rate is higher. In the latter case, the sampled signal actually looks like a sine wave.

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1 Introduction to Data Acquisition

How Can Aliasing Be Eliminated?

The primary considerations involved in antialiasing are the sampling rate of the A/D converter and the frequencies present in the sampled data. To eliminate aliasing, you must

• Establish the useful bandwidth of the measurement.

• Select a sensor with sufficient bandwidth.

• Select a low-pass antialiasing analog filter that c an eliminate all

frequencies exceeding this bandwidth.

• Sample the data at a rate at least twice that of the filter’s upper cutoff

frequency.

1-44

Getting Command-Line Function Help

To get command-line function help, you should use the daqhelp function. For example, to get help for the

daqhelp addchannel

Alternatively, you can use the h elp command.

help addchannel

However, the Data Acquisition To olbo x software provides “overloaded” versions of several MATLAB functions. That is, it provides toolbox-specific implementations of these function s using the same function name. To get command-line help for an overloaded toolbox function using the command, you must supply one of two possible class directories to help:

help daqdevice/function_name help daqchild/function_name

addchannel function, type

Getting Command-Line Function Help

help

Note that the same help information is returned regardless of the class directory specified.

For example, the Data Acquisition Toolbox softw are provides an overloaded version of the

delete function. To obtain help for the MATLAB version

of this function, type

help delete

You can determine if a function is overloaded by examining the last section of the help. For

delete, the help contains the following overloaded versions

(not all are show n):

Overloaded methods help char/delete.m help scribehandle/delete.m help daqdevice/delete.m help daqchild/delete.m

So, to obtain help on the toolbox version of this function, type

help daqdevice/delete

1-45

1 Introduction to Data Acquisition

Selected Bibliography

[1] Transducer Interfacing Handbook — A Guide to Analog Signal Conditioning, edited by Daniel H. Sheingold; Analog D evices Inc., Norwood,

MA, 1980.

[2] Bentley, John P., Principles of Measurement Systems, Second Edition; Longman Scientific and Technical, Harlow, Essex, UK, 1988.

[3] Bevington, Philip R., Data Reduction and Error Analysis for the Physical Sciences; McGraw-Hill, N ew York, NY, 1969.

[4] Carr, Joseph J., Sensors; Prompt Publications, Indianapolis, IN, 1997.

[5] The Measurement, Instrumentation, and Sensors Handbook,editedby John G. Webster; CRC Press, Boca Raton, FL, 1999.

[6] PCI-MIO E Series User Manual, January 1997 Edition; Part Number 320945B-01, National Instruments, Austin, TX, 1997.

1-46

Using Data Acquisition Toolbox Software

This chapter provides the information you need to get started with Data Acquisition Toolbox software. The sections are as follows.

• “Installation Information” on page 2-2

• “Toolbox Components” on page 2-4

• “Accessing Your Hardware” on page 2-12

• “Understanding the Toolbox Capabilities” o n page 2-19

• “Examining Your Hardware Resources” on page 2-21

• “Getting Help” on page 2-25

2 Using Data Acquisition Toolbox™ Software

Installation Information

In this section...

“Prerequisites” on page 2-2

“Toolbox Installation” on page 2-2

“Hardware and Driver Installation” on page 2 -3

Prerequisites

To acquire live, measured data into the MATLAB workspace, or to output data from the MATL AB software, you must install these com ponents:

• MATLAB

• Data Acquisition Toolbox

• A supported data acquisition device (the toolbox page on

theMathWorksWebsitelistsallsupporteddevicesat

http://www.mathworks.com/products/daq/supportedio.html)

2-2

• Software such as drivers and support libraries, as required by your data

acquisition device

Note If you have a hardware that is not supported by Data Acquisition Toolbox, see “Unsupported Hardware” on page 2-11.

Toolbox Installation

To determine if the Data Acquisition Toolbox software is installed on your system, type

ver

at the MATLAB prompt. The MATLAB Command Window lists information about the software versions you are running, including installed add-on products and their version numbers. Check the list to see if the Data Acquisition Toolbox product appears. For information about installing the toolbox, see the MATLAB Installation Guide for your platform.

Installation Information

If you experience installation difficulties and have Web access, look for the license manager and installation information at the MathWorks Web site (

http://www.mathworks.com).

Hardware and Driver Installation

Installation of your hardware device, hardware drivers, and any other device-specific software is described in the documentation provided by your hardware vendor.

Note You need to install all necessary device-specific software provided by your hardware vendor in addition to the Data Acquisition Toolbox software.

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2 Using Data Acquisition Toolbox™ Software

Toolbox Components

In this section...

“Information and Interaction” on page 2-4

“MATLAB Functions” on page 2-6

“Data Acquisition Engine” on page 2-6

“Hardware Driver Adaptor” on page 2-9

“Supported Hardware” on page 2-9

“Unsupported Hardware” on page 2-11

Information and Interaction

The Data Acquisition Toolbox software consists of three distinct components:

• MATLAB functions

2-4

• the data acquisition engine

• hardware driver adaptors

As shown in the figure, these components allow you to pass information between the MATLAB workspace and your data acquisition hardware.

Toolbox Components

The preceding diagram illustrates how information flows from component to component. Information consists of:

• Property values – You can control the behavior of your data acquisition

application by configuring property values. In general, you can think of a property as a characteristic of the toolbox or of the hardware driver that can be manipulated to suit your needs.

2-5

2 Using Data Acquisition Toolbox™ Software

• Data – You can acquire data from a sensor connected to an analog input

subsystem and store it in the MATLAB workspace, or output data from the MATLAB workspace to an actuator connected to an analog output subsystem. Additionally you can transfer values (1s and 0s) between the MATLAB workspace and a digital I/O subsystem.

• Events – An event occurs at a particular time after a condition is met

and might result in one or more callbacks that you specify. Events can be generated only after you configure the associated propertie s. Some ways you can use events include initiating analysis after a predetermined amount of data is acquired, or displaying a message to the MATLAB workspace after an error occurs.

MATLAB Functions

To perform any task with your data acquisition application, you must call MATLAB functions from the MATLAB environment. Among other things, these functions allow you to:

• Create device objects, which provide a gateway to your hardware’s

capabilities and allow you to control the behavior of your application.

2-6

• Acquire or output data.

• Configure property values.

• Evaluate your acquisition status and hardware resources.

For a listing of all Data Acquisition Toolbox functions, refer to Chapter 13, “Functions — Alphabetical List”. You can also display all these functions by typing

help daq

Data Acquisition Engine

The data acquisition engine (or just engine) is a MEX-file (shared library that is executable within the MATLAB software) that

• Stores the device objects and associated property values that control your

data acquisition application

• Controls the synchronization of events

Toolbox Components

• Controls the storage of acquired or queued data

While the engine performs these tasks, you can use MATLAB for other tasks such as analyzing acquired data. In other words, the engine and the MATLAB software are asynchronous. The relationship between acquiring data, outputting data, and data flow is described next.

Flow of Acquired Data

Acquiring data means that data is flowing from your hardware device into the data acquisition engine where it is temporarily stored in memory, until you explicitly extract it using the

If you do not extract this data, and the amount of data stored in memory reaches the limit for the data acquisition object (see DataMissed event occurs. At this point, the acquisition stops.

Therateatwhichtheacquisitionstopsdepends on several factors including the available memory, the rate at which data is acquired, and the number of hardware channels from which data is acquired.

getdata function.

daqmem(obj)), a

The flow of acquired data consists of these two independent steps:

1 Data acquired from the hardware is stored in the engine.

2 Data is extracted from the engine and stored in the MATLAB workspace,

or output to a disk file.

These two steps are illustrated below.

2-7

2 Using Data Acquisition Toolbox™ Software

Flow of Output Data

Outputting data means that data is flowing from the data acquisition engine to the hardware device. However, before data is output, you must queue it in theenginewiththe depends on several factors including the available memory, the number of hardware channels to which data is output, and the size of each data sample.

putdata function. The amount of data that you can queue

2-8

The flow of output data consists of these two independent steps:

1 Data from the MATLAB workspace is queued in the engine.

2 Data queued in the engine is output to the hardware.

These two steps are illustrated below.

Toolbox Components

Hardware Driver Adaptor

The hardware driver adaptor (or adaptor) is the interface between the data acquisitionengineandthehardwaredriver. Theadaptor’smainpurposeisto pass information between MATLAB and your hardware device via its driver.

Hardware drivers are provided by your device vendor. For e xample, to acquire data using a National Instruments board, the appropriate version of the NI-DAQ driver must be installed on your platform. For further information about NI-DAQmx and Traditional NI-DAQ drivers, see “NI-DAQmx Versus Traditional NI-DAQ Drivers” on page A-7. Hardware drivers are not installed as part of the toolbox with the exception of a special parallel port driver that allows access to the port’s protected memory addresses. Additionally, a suitable driver is usually installed on PCs that are equipped with a sound card. For the remaining supported devices, the drivers must be installed.

Supported Hardware

You can obtain most adaptors either from the MathWorks or from the device vendors. Se e the supported hardware page at

www.mathworks.com/products/daq/supportedio.html for a list of vendors

whose hardware the toolbox supports, and for information about how to

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2 Using Data Acquisition Toolbox™ Software

obtain an adaptor. The toolbox provides the following adaptors. The name of the vendor or device is also listed in the table.

Adaptor Provided by the Data Acquisition Device

Vendor or Device Adaptor Name

Advantech

Measurement Computing

National Instruments NI-DAQmx adaptors

National Instruments Traditional NI-DAQ adaptors

Parallel port

Windows sound cards

advantech

mcc

nidaq

parallel

winsound

2-10

Notes The Traditional NI-DAQ adaptor will be deprecated in a future version of the toolbox. If you create a Data Acquisition Toolbox™ object for Traditional NI-DAQ adaptor beginning in R2008b, you will receive a warning stating that this adaptor will be removed in a future release. See the supported hardware page at

www.mathworks.com/products/daq/supportedio.html

for more information.

The Parallel adaptor will be deprecated in a future version of the toolbox. If you create a Data Acquisition Toolbox™ o bject for

'parallel'

beginning in R2008b, you will receive a warning stating that this adaptor will be removed in a future release. See the supported hardware page at

www.mathworks.com/products/daq/supportedio.html for more

information.

Toolbox Components

Note Additional vendors not in this table are listed in the supported hardware page at

www.mathworks.com/products/daq/supportedio.html.

This page contains a comprehensive list of vendors whose hardware the toolbox supports, and it provides information on how to obtain an adaptor.

As described in “Examining Your Hardware Resources” on page 2-21, you can list the installed adaptor names with the

daqhwinfo function.

Unsupported Hardware

Refer to the supported hardware page for Data Acquisition Toolbox software at

www.mathworks.com/products/daq/supportedio.html for the list of

vendors whose hardware the toolbox supports, and for information about how to obtain an adaptor. If the device you are using is not listed on this page, you candooneofthefollowing:

• Contact the device vendor to request them to develop an interface

to the toolbox. Refer them to the s upported hardware page at

www.mathworks.com/products/daq/supportedio.html for a list of

currently supported hardware and for information about contacting The MathWorks.

• Search for your device on The MathWorks support page at

www.mathworks.com/support/ to see if a solution is listed for using your

unsupported device. Such solutions are typically available for devices that the next Data Acquisition Toolbox release will support.

• Create the interface yourself. To interface unsupported hardware devices

to the toolbox, use the Data Acquisition Toolbox Adaptor Kit installed with the toolbox. For more information about the adaptor kit, read the Data Acquisition Toolbox Adaptor Kit User’s Guide.

• Hire a consultant to write the interface or a systems integrator

to build the system. For a potential list of consultants or systems integrators, go to the Third Party Products and Services page at

www.mathworks.com/connections.

• Consider using hardware that the toolbox already supports.

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2 Using Data Acquisition Toolbox™ Software

Accessing Your Hardware

In this section...

“Connecting to Your Hardware” on page 2-12

“Acquiring Data” on page 2-12

“Outputting Data” o n page 2-13

“Reading and Writing Digital Values” on page 2-14

“Acquiring Data in a Loop” on page 2-17

Connecting to Your Hardware

Perhaps the most effective way to get started with Data Acquisition Toolbox software is to connect to your hardware, and input or output data.

Each example illustrates a typical data acquisition session.Thedata acquisition session comprises all the steps you are likely to take when acquiring or outputting data using a supported hardware device. You should keep these steps in mind when constructing your own data acquisition applications.

2-12

Note that the analog input and analog output examples use a sound card, while the digital I/O example uses a National Instruments PCI-6024E board. If you are using a different supported hardware device, you should modify the adaptor name and the device ID supplied to the creation function as needed.

If you want detailed information about any functions that are used, refer to Chapter 13, “Functions — Alphabetical List”. If you want detailed information about any properties that are used, refer to Chapter 15, “Base Properties — Alphabetical List”.

Acquiring Data

If you have a sound card installed, you can run the following example, which acquires 1 second of data from two analog input hardware channels, and then plots the acquired data.

Accessing Your Hardware

You should modify this example to suit your specific application needs. If you want detailed inform ation about acquiring data, refer to Doing More with Analog Input.

1 Create a device object — Create the analog input object ai for a sound

card.

ai = analoginput('winsound');

2 Add channels — Add two hardware channels to ai.

addchannel(ai,1:2);

3 Configure property values — Configure the sampling rate to 44.1 kHz

and collect 1 second of data (44,100 samples) for each channel.

set(ai,'SampleRate',44100) set(ai,'SamplesPerTrigger',44100)

4 Acquire data — Start the acquisition and issue wait to block the

MATLAB Command Window until all data is acquired. When all the data is acquired,

wait returns and the data is then available to getdata.

start(ai) wait(ai,2) data = getdata(ai); plot(data)

5 Clean up — When you no longer need ai, you should remove it from

memory and from the MATLAB workspace.

delete(ai) clear ai

Outputting D

If you have a outputs 1 se

You should you want de “Analog Ou

cond of data to two analog output hardware channels.

modify this example to suit your specific application needs. If

tailed information about outputting data, refer to Chapter 6,

tput”.

ata

sound card installed, you can run the following example, which

2-13

2 Using Data Acquisition Toolbox™ Software

1 Create a device object — Create the analog output object ao for a sound

card.

ao = analogoutput('winsound');

2 Add channels — Add two hardware channels to ao.

addchannel(ao,1:2);

3 Configure property values — Configure the sampling rate to 44.1 kHz

for each channel.

set(ao,'SampleRate',44100)

4 Output data — Create 1 second of output data, and queue the data in

the engine for eventual output to the analog output subsystem. You must queue one column of data for each hardware channel added.

data = sin(linspace(0,2*pi*500,44100)'); putdata(ao,[data data])

2-14

Start the output. When all the data is output, ao automatically stops executing.

start(ao)

5 Clean up — When you no longer need ao, you should remove it from

memory and from the MATLAB workspace.

delete(ao) clear ao

Reading and Writing Digital Values

If you have a supported National Instruments board with at least two digital I/O ports, you can run the following example, which writes and reads digital values.

You sho uld modify this example to suit your specific application needs. Adjust the example if the ports on your device do not support the input/output directions specified here.

Accessing Your Hardware

If you want detailed information about reading and writing digital values, refer to Digital Input/Output.

1 Create a device object — Create the digital I/O object dio for a National

Instruments U SB -6212 board with hardware ID Dev1.

dio = digitalio('nidaq','Dev1');

2 Add output lines — Add four lines from port 0 to dio, and configure

them for output.

addline(dio,0:3, 0,'out');

3 Add input lines — Add two lines from port 1 to dio, and configure them

for input.

addline(dio,0:1, 1,'in');

To display a summary of the digital I/O object, type:

dio

%display returns the following

Display Summary of DigitalIO (DIO) Object Using 'USB-6212'.

Port Parameters: Port 0 is port configurable for reading and writing.

Port 1 is port configurable for reading and writing.

Port 2 is port configurable for reading and writing.

Engine status: Engine not required.

DIO object contains line(s):

Index: LineName: HwLine: Port: Direction:

1 '' 0 0 'Out'

2 '' 1 0 'Out'

3 '' 2 0 'Out'

4 '' 3 0 'Out'

5 '' 0 1 'In'

6 '' 1 1 'In'

2-15

2 Using Data Acquisition Toolbox™ Software

4 Write values — Create an array of output values, and write the values to

the digital I/O subsystem. Note that reading and writing digital I/O line values typically does not require that you configure specific property values.

pval = [1 1 0 1]; putvalue(dio.Line(1:4),pval)

5 Read values— To read only the input lines, type:

gval = getvalue(dio.Line(5:6))

%input lines values displayed gval =

To read both input and output lines, type:

gval = getvalue(dio)

%input and output lines va lue s displayed gval =

110100

2-16

When you read output lines getvalue returns the most recently output value set by

6 Clean up — When you no longer need dio, you should remove it from

putvalue.

memory and from the MATLAB workspace.

delete(dio) clear dio

Note Digital line values are usually not transferred at a specific rate. Although some specialized boards support clocked I/O, the Data Acquisition Toolbox software does not support this functionality.

Accessing Your Hardware

Acquiring Data in a Loop

To make multiple acquisitions using a single analog input object, create a single object and execute the acquisition in a loop. Delete the object at the end of the loop.

% Create the object outside of the loop. ai = analoginput('nidaq', 'Dev1'); addchannel(ai, 0); % Execute acquisition. for ii = 1:num_iterations

start(ai);

wait(ai, 2) data = getdata(ai);

plot(data); end % Delete the object out of the loop. delete(ai) clear ai

If you are creating the object within the loop, you must delete the object within the loop as well.

% Execute acquisition. for ii = 1:num_iterations

% Create the object within the loop.

ai = analoginput('nidaq', 'Dev1');

addchannel(ai, 0);

start(ai);

wait(ai, 2)

data = getdata(ai);

plot(data);

% Delete the object within the loop.

delete(ai) end clear ai

Note Make sure you delete the object within the loop as it can consume system resources.

2-17

2 Using Data Acquisition Toolbox™ Software

For more information about cleaning up the MATLAB workspace, refer to Cleaning Up.

2-18

Understanding the Toolbox Capabilities

In this section...

“Contents File” on page 2-19

“Documentation Examples” on page 2-19

“Quick Reference Guide” on page 2-20

“Demos” on page 2-20

Contents File

The Contents file lists the toolbox functions and demos. You can display this information by typing:

help daq

Documentation Examples

This guide provides detailed examples that show you how to acquire or output data. These examples are collected in the index.

Understanding the Toolbox Capabilities

Some examples are constructed as mini-applications that illustrate one or two important features of the toolbox and serve as templates so you can see how to build applications that suit your specific needs. These examples are included as to olbo x files and are treated as demos. You can list all Data Acquisition Toolbox demos by typing

help daqdemos

All documentation e xample files begin with daqdoc. To run an example, type the file name at the command line. Note that most analog input (AI) and analog output (AO) examples are written for sound cards. To use these examples with your hardware device, you should modify the adaptor name and the device ID supplied to the creation function as needed.

Additionally, most documentation examples are written for clocked subsystems. However, some supported hardware devices—particularly Measurement Computing devices—do not possess onboard clocks. If the AI or AO subsystem of your hardware device does not have an onboard clock, then these examples will not work. To use the documentation examples, you can:

2-19

2 Using Data Acquisition Toolbox™ Software

• Input single values using the getsampl e function, or output single values

using the

putsample function.

• Configure the

ClockSource property to Software.

Quick Reference Guide

The Quick Reference Guide provides an overview of the toolbox capabilities, functions, and properties. You might find it useful to print this guide and keep it handy when using the toolbox. You can access this guide through the Help browser.

Demos

The toolbox includes a large collection of tutorial demos, which you can access through the Help browser Demos pane. Use the following command to open the Help browser to the toolbox demos:

demo toolbox 'Data Acquisition'

Note that the analog input and analog output tutorials require that you have a sound card installed. The digital I/O tutorials require that you have a supported National Instruments board with digital I/O capabilities.

2-20

Examining Your Hardware Resources

In this section...

“Using the daqhwinfo Function” on page 2-21

“General Toolbox Information” o n page 2-21

“Adaptor-Specific Information” on page 2-22

“Device Object Information” on page 2-23

Using the daqhwinfo Function

You can examine the data acquisition hardware resources visible to the toolbox with the boards, hardware drivers, and adaptors. The information returned by

daqhwinfo depends on t h e supplied arguments, and is divided into three

categories described in this section.

If you configure hardware parameters using a vendor tool such as N ational Instruments Measurement and Automation Explorer or Measurement Computing InstaCal, For example, if you configure your Measurement Computing device for 16 single-ended channels using InstaCal, However, the toolbox does not preserve configuration information that is not directly associated with your hardware. For example, channel name information is not preserved. Refer to Appendix A, “Troubleshooting Your Hardware” for more information about using vendor tools.

daqhwinfo function. H ard w are resources include in sta lled

daqhwinfo will return this configuration information.

daqhwinfo returns this configuration.

Examining Your Hardware Resources

General Toolbox Information

To display general information about the toolbox, enter:

out = daqhwinfo out =

ToolboxName: 'Data Acquisition Toolbox'

ToolboxVersion: '2.2 (R13)'

MATLABVersion: '6.5 (R13)'

InstalledAdaptors: {4x1 cell}

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2 Using Data Acquisition Toolbox™ Software

The InstalledAdaptors field lists the hardware driver adaptors installed on your system. To display the installed adaptors, enter:

out.InstalledAdaptors ans =

'mcc' 'nidaq' 'parallel' 'winsound'

This information tells you that an adaptor is available for Measurement Computing and National Instruments devices, parallel ports, a nd sound cards.

Notes The list of installed adaptors might differ for your platform. Toolbox adaptors are available to you only if the associated hardware driver is installed.

The Traditional NI-DAQ adaptor will be deprecated in a future version of the toolbox. If you create a Data Acquisition Toolbox™ object for Traditional NI-DAQ adaptor beginning in R2008b, you will receive a warning stating that this adaptor will be remo ved in a future release.

2-22

The Parallel adaptor will be deprecated in a future version of the toolbox. If you create a Data Acquisition Toolbox™ o bject for

'parallel'

beginning in R2008b, you will receive a warning stating that this adaptor will be removed in a future release. See the supported hardware page at

www.mathworks.com/products/daq/supportedio.html for more

information.

Adaptor-Specific Information

To display hardware information for a particular vendor, you must supply the adaptor name as an argument to and adaptor names are given in Hardware Driver Adaptor. For example, to display hardware information for the

out = daqhwinfo('winsound') out =

AdaptorDllName: 'd:\v6\toolbox\daq\daq\private\mwwinsou nd.dll'

daqhwinfo. The supported vendors

winsound adaptor, enter:

Examining Your Hardware Resources

AdaptorDllVersion: 'Version 2.2 (R13) 01-Jul-2002'

AdaptorName: 'winsound'

BoardNames: {'AudioPCI Record'}

InstalledBoardIds: {'0'}

ObjectConstructorName:{'analoginput('winsound',0)'[1x26 char]}

The ObjectConstructorName field lists the subsystems supported by the installed sound cards, and the syntax for creating a device object associated with a given subsystem. To display the device object constructor names available for the AudioPCI Record board, enter:

out.ObjectConstructorName(:) ans =

'analoginput('winsound',0)' 'analogoutput('winsound',0)'

This information tells you that the sound card supports analog input and analog output objects. To create an analog input object for the sound card, enter:

ai = analoginput('winsound');

To create an analog output object for the sound card, enter:

ao = analogoutput('winsound');

Device Object Information

To display hardware information for a specific device object, you supply the device object as an argument to analog input object

ai created in the “Adaptor-Specific Information” on page

2-22 section is given below.

out = daqhwinfo(ai) out =

AdaptorName: 'winsound'

DeviceName: 'AudioPCI Record'

DifferentialIDs: []

daqhwinfo. The hardware information for the

Bits: 16

Coupling: {'AC Coupled'}

Gains: []

ID: '0'

2-23

2 Using Data Acquisition Toolbox™ Software

VendorDriverDescription: 'Windows Multimedia Driver'

VendorDriverVersion: '5.0'

Among other things, this information tells you that the minimum sampling rate is 8 kHz, the maximum sampling rate is 44.1 kHz, and there a re two hardware channels that you can add to the analog input object.

Alternatively, you can return hardware information via the Workspace browser by right-cli cking a device object, and selecting Explore > Display Hardware Info from the context menu.

InputRanges: [-1 1] MaxSampleRate: 44100 MinSampleRate: 8000

NativeDataType: 'int16'

Polarity: {'Bipolar'}

SampleType: 'SimultaneousSample'

SingleEndedIDs: [1 2]

SubsystemType: 'AnalogInput' TotalChannels: 2

2-24

Getting Help

In this section...

“The daqhelp Function” on page 2-25

“The propinfo Function” on page 2-25

The daqhelp Function

You can use the daqhelp function to:

• Display help for functions and properties.

• List all the functions and properties associated with a specific device object

A device object nee d not exist for you to obtain this information. For e xample, to display all the functions and properties associated with an analog input object, as well as the constructor help, enter:

daqhelp analoginput

To display help for the Samp leRa te property

daqhelp SampleRate

You can also display help for an existing dev ice object. For example, to display help for the with a sound card

ai = analoginput('winsound'); out = daqhelp(ai,'BitsPerSample');

Alternatively, you can display help via the Workspace browser by right-clicking a device object, and selecting Explore > DAQ Help from the context menu.

BitsPerSample property for an analog input object associated

The propinfo Function

You can use the propinfo function to return the characteristics of toolbox properties. For example, you can find the default value for any property using this function.

propinfo returns a structure containing the following fields:

2-25

2 Using Data Acquisition Toolbox™ Software

propinfo Fields

Field Name Description

Type

Constraint

ConstraintValue

DefaultValue

ReadOnly

DeviceSpecific

The property data type. Possible values are callback,

any, double,andstring.

The type of constraint on the property value. Possible values are

callback, bounded, enum,andnone.

The property value constraint. The constraint can be a range of valid values or a list of valid string values.

The property default value.

Indicates when the property is read-only. Possible values are

always, never,andwhileRunning.

If the property is device-specific, a 1 is returned. If a

0 is returned, the property is supported for all device

objects of a given type.

2-26

For example, to return the characteristics for all the properties associated with the analog input object

ai created in the “The daqhelp Function” on

page 2-25 section, enter:

AIinfo = propinfo(ai);

The characteristics for the TriggerType property are displayed below.

AIinfo.TriggerType ans =

Type: 'string'

Constraint: 'enum'

ConstraintValue: {'Manual' 'Immediate' 'Software'}

DefaultValue: 'Immediate'

ReadOnly: 'whileRunning'

DeviceSpecific: 0

This information tells you that:

• The property value data type is a string.

• The property value is constrained as an enumerated list of values.

Getting Help

• The three possible property values are

• Thedefaultvalueis

Immediate.

Manual, I mmediate,andSoftware.

• The property is read-only while the device object is running.

• The property is supported for all analog input objects.

2-27

2 Using Data Acquisition Toolbox™ Software

2-28

Data Acquisition Session

The data acquisition session consists of all the steps you are like ly to take when acquiring or outputting data. These steps are described in the following sections.

• “Understanding the Data Acquisition Session” on page 3-2

• “Creating a Device Object” on page 3-6

• “Hardware Channels or Lines” on page 3-10

• “Configuring and Returning Properties” on page 3-14

• “Acquiring and Outputting Data” on page 3-24

• “Cleaning Up” on page 3-28

3 Data Acquisition Session

Understanding the Data Acquisition Session

In this section...

“Overview” on page 3-2

“Real-Time Data Acquisition” on page 3-3

“Example: The Data Acquisition Session” on page 3-4

Overview

The data acquisition session consists of all the steps you are like ly to take when acquiring or outputting data. These steps are

1 Create a device object — You create a device object using the

analoginput, analogoutput,ordigitalio creation function. Device

objects are the basic toolbox elements you use to access your hardware device.

3-2

2 Add channels or lines — After a device object is created, you must add

channels or lines to it. Channels are added to analog input and analog output objects, while lines are added to digital I/O objects. Channels and lines are the basic hardware device elements with which you acquire or output data.

3 Config

assig

You can configure many of the properties at any time. However, some properties are configurable only when the device object is not running. Conversely, depending on your hardware settings and the requirements of your application, you might be able to accept the default property values andskipthisstep.

4 Queue data (analog output only) — Before you can output analog data,

you must queue it in the engine with the

5 Sta

mu ou

ure properties — To establish the device object behavior, you

n values to properties using the

rt acquisition or output of data — To acquire or output data, you

st execute the device object with the

tput occurs in the background, while MATLAB continues executing. You

set function or dot notation.

putdata function.

start function. Acquisition and

Understanding the Data A cquisition Session

can e xecute other MATLAB commands while the acquisition is occurring, and then wait for the acquisition or output to complete.

6 Wait for the acquisition or output to complete — You can continue

working in the MATLAB workspace while the toolbox is acquiring or outputting data. (For more information,seeChapter5,“DoingMorewith Analog Input”.) However, in many cases, you simply want to wait for the acquisition or output to complete before continuing. Use the

wait function

to pause MATLAB until the acquisition is complete.

7 Extract your acquired data (analog input only) — After data is acquired,

you must extract it from the engine with the

8 Clean up — When you no longer need the device object, you should

remove it from memory using the MATLAB workspace using the

delete function, and remove it from the

clear command.

getdata function.

The data acquisition session is used in many of the do cumentation examples included in this guide. Note that the f ourth step is treated differently for digital I/O objects because they do not store data in the engine. Therefore, only analog input and analog output objects are discussed in this section.

Real-Time Data Acquisition

Because it is operating on a consumer operating system, the Data Acquisition Toolbox cannot ensure response to an event within a specified maximum time limit. In order to ensure a high throughput of the acquisition, the toolbox manages acquired data in blocks, which increases the latency associated with any given acquired data point. In addition, it must share system resources with other applications and drivers on the system.

If you want to create a control loop with the least latency, and do not require a deterministic response time, you can perform single point operations using

getsample and putsample. In this case, the data is acquired and processed as

follows:

1 Data is acquired through your hardware vendor’s software.

2 The data is then handed off to the Data Acquisition Toolbox engine.

3 The toolbox makes the data available in MATLAB or Simulink.

3-3

3 Data Acquisition Session

4 The data is run through the control algorithm that you develop in MATLAB

or Simulink.

5 Thedataisthenroutedbacktotheengine,throughthehardwarevendor’s

software, and onto the board.

This still does not guarantee the response time of a control loop. A higher priority thread can take precedence over the control loop.

Most PC based data acquisition cards provide an internal, high accuracy clock that is used to pace data acquisition. Th ecardsstorethedatatheycollectin local memory, and then transfer the samples to main c ompute r memory (using interrupts or DMA). The timing of samples acquired this way is extremely accurate, and these cards can guarantee that the acquired data was obtained at the requested sample rate, and that no samples were dropped. The maximum sampling rate is governed by the data acquisition card, not the PC.

For true real-time closed loop control with MATLAB, consider some of these other MathWorks products:

3-4

• Real-Time Workshop

• Real-Time Windows Target for Real-Time Workshop

• xPC Target

Example: The Data Acquisition Session

This example illustrates the basic steps you take during a data acquisition session using an analog input object. You can run this example by typing

daqdoc3_1 at the MATLAB Command Window.

1 Create a device object — Create the analog input object AI for a sound

card. The installed adaptors and hardware IDs are found with

AI = analoginput('winsound'); %AI = analoginput('nidaq','Dev1'); %AI = analoginput('mcc',1);

2 Add channels — Add two channels to AI.

addchannel(AI,1:2);

daqhwinfo.

Understanding the Data A cquisition Session

%addchannel(AI,0:1); % For NI and MCC

3 Configure property values — Configure the sampling rate to 11.025 kHz

and define a 2 second acquisition.

set(AI,'SampleRate',11025) set(AI,'SamplesPerTrigger',22050)

4 Start acquisition —Beforethestart function is issued, you might want

to begin inputting data from a microphone or a CD player.

start(AI)

5 Wait for the acquisition or output to complete — Pause MATLAB

until either the acquisition completesor3secondshaveelapsed(whichever comes first). If 3 seconds elapse, an error occurs.

wait(AI,3);

6 Extract the acquired data from the engine and plot results

data = getdata(AI);

Plot the data and label the figure axes.

plot(data) xlabel('Samples') ylabel('Signal (Volts)')

7 Clean up — When you no longer need AI, you should remove it from

memory and from the MATLAB workspace.

delete(AI) clear AI

3-5

3 Data Acquisition Session

Creating a Device Object

In this section...

“Understanding Device Objects” on page 3-6

“Creating an Array of Device Objects” on page 3-7

“Where Do Device Objects Exist?” on page 3-8

Understanding Device Objects

Device objects are the toolbox components you use to access your hardware device. They provide a gateway to the functionality of your hardware, and allow you to control the behavior of your data acquisition application. Each device object is associated with a specific hardware subsystem .

To create a device object, you call functions called object creation functions (or object constructors). These functions are implemented using the object-oriented programming capabilities provided by the MATLAB software, which are described in the chapters “Classes (Data Types)” and “Using Objects” in the MATLAB Programming Fundamentals documentation. The device object creation functions are listed below.

3-6

Device Object Creation Functions

Functi

ginput

analo

ogoutput

anal

talio

digi

Before you can create a device object, the associated hardware driver adaptor must be registered. Adaptor registration occurs automatically. However, if for some reason an adaptor is not automatically registered, then you must do so manually with the Driver Adaptor” on page A-19 for more information.

You can find out how to create device objects for a particular vendor and subsystem with the

daqregister function. Refer to “Registering the Hardware

ObjectConstructorName field of the daqhwinfo function.

Descri

Creat

Crea

ption

e an analog input object.

te an analog output object.

te a digital I/O object.

Creating a Device Object

For example, to find out how to create an analog input object for an installed National Instruments board, you supply the appropriate adaptor name to

daqhwinfo.

out = daqhwinfo('nidaq'); out.ObjectConstructorName(:) ans =

'analoginput('nidaq','Dev1')' 'analogoutput('nidaq','Dev1')' 'digitalio('nidaq','Dev1')'

The constructor syntax tells you that you must supply the adaptor name and the hardware ID to the

ai = analoginput('nidaq','Dev1');

analoginput function

The association between device objects and hardware subsystems is shown below.

Creating an Array of Device Objects

In the MATLAB workspace, you can create an array from existing variables by concatenating those variables together. The same is true for device objects. For example, suppose you create the analog input object output object

ao for a sound card:

ai and the analog

3-7

3 Data Acquisition Session

ai = analoginput('winsound'); ao = analogoutput('winsound');

You can now create a device object array consisting of ai and ao using the usual MATLAB syntax. To create the row array

x=[aiao]

Index: Subsyste m: Name: 1 Analog Input winsound0-AI 2 Analog Output winsound0-AO

To create the column array y:

y = [ai;ao];

Note that you cannot create a matrix of device objects. For example, you cannot create the matrix

3-8

z = [ai ao;ai ao]; ??? Error using ==> analog inp ut/vertcat Only a row or column vector of device objects can be created.

Depending on your application, you might want to pass an array of device objects to a function. For example, using one call to the configure b oth

set(x,'SampleRate',44100)

ai and ao to the same property value.

set function, you can

Refer to Chapter 13, “Functions — Alphabetical List” to see which functions accept a device object array as an input argument.

Where Do Device Objects Exist?

When you create a device object, it exists in b oth the MATLAB workspace and the data acquisition engine. For example, suppose you create the analog input object

ai for a sound card and then make a copy of ai.

ai = analoginput('winsound'); newai = ai;

Mathworks CURVE FITTING TOOLBOX RELEASE NOTE

Specifications and Main Features

Frequently Asked Questions

User Manual

Introduction to Data Acquisition

Product Overview

Understanding Data Acquisition Toolbox Software

Exploring the Toolbox

Anatomy of a Data Acquisition Experiment

System Setup

Calibration

Trials

Data Acquisition System

Overview

Analog Input Subsystems

Analog Output Subsystems

Digital Input/Output Subsystems

Counter/Timer Subsystems

Sensors

Common Analog Sensors

Sensor Output

Sensor Bandwidth

Signal Conditioning

Amplification

Filtering

Electrical Isolation

Multiplexing

Excitation Source

The Computer

Software

Application Software

Analog Input Subsystem

Function of the Analog Input Subsystem

Sampling

Scanning Hardware

Simultaneous Sample and Hold Hardware

Quantization

Quantization Error

Input Range and Polarity

How Are Acquired Samples Clocked?

Channel Configuration

Differential Inputs

Single-Ended Inputs

Transferring Data from Hardware to System Memory

FIFO Buffer

Interrupts

Making Quality M easurements

What Do You Measure?

Accuracy and Precision

Accuracy

Precision

How Are Range, Gain, and Measurement Precision Related?

Relationship Between Input Range, Gain, and Precision

Noise

Removing Internal Noise

Removing External Noise

Filtering

Matching the Sensor Range and A/D Converter Range

How F ast Should a Signal Be Sampled?

How Can Aliasing Be Eliminated?

Getting Command-Line Function Help

Selected Bibliography

Using Data Acquisition Toolbox Software

Installation Information

Prerequisites

Toolbox Installation

Hardware and Driver Installation

Toolbox Components

Information and Interaction

MATLAB Functions

Data Acquisition Engine

Flow of Acquired Data

Flow of Output Data

Hardware Driver Adaptor

Supported Hardware

Adaptor Provided by the Data Acquisition Device

Unsupported Hardware

Accessing Your Hardware

Connecting to Your Hardware

Acquiring Data