Adafruit CLUE Metal Detector User Manual

CLUE Metal Detector in CircuitPython

Created by Kevin Walters

Last updated on 2021-02-08 06:48:17 PM EST

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Guide Contents

Guide Contents Overview

Parts

CLUE version Circuit Playground Bluefruit with TFT Gizmo version Circuit Playground Bluefruit only version Common

Design

Inductance and Permeability Metal Detection

Beat Frequency From An Oscillator Pair RLC Filters Charging a Capacitor with RLD Continuous Charge/Discharge with RLD Two Coil Systems

CLUE Metal Detector

Microcontrollers vs Inductors

Microcontrollers vs Inductors GPIO Protection Larger Coil Currents

Circuit

Components Coil Construction Circuit Construction

CLUE board Circuit Playground Bluefruit with TFT Gizmo Circuit Playground Bluefruit board only

CircuitPython on CLUE

Set up CircuitPython Quick Start!

CircuitPython on Circuit Playground Bluefruit Install or Update CircuitPython CircuitPython

Libraries

Libraries for Metal Detector for CLUE Libraries for Metal Detector for Circuit Playground Bluefruit with TFT Gizmo

Development Testing

Metal Detector

Example Video Troubleshooting Operation Code Code Discussion

Voltage from ADC Values Using Global Variables in Python Positional Arguments Practical Issues with displayio Graphics Filters with and without ulab Library Magnetometer Baseline and Code Reviews

ADC Analysis

Voltage across Capacitor in the Metal Detector

Going Further

Ideas for Areas to Explore Related Projects Further Reading

Overview

This project creates a metal detector using an Adafruit CLUE with a few common components and an

easy-to-make coil.

The program is written in CircuitPython for version 5.1.0 or later. The code also runs on the Circuit

Playground Bluefruit (CPB) with the TFT Gizmo screen. The program can be used without a screen on the

CPB in audio/light mode only.

Alligator clips to male jumpers can be used with or without the Adafruit Dragontail to connect the CLUE

and the coil to the breadboard. The pictures feature alternate products.

This project was inspired by an old Ray Marston book featuring a metal detector project and the

Detectorists (https://adafru.it/L7d) BBC TV series.

Parts

CLUE version

1 x Adafruit CLUE

Adafruit CLUE - nRF52840 Express with Bluetooth LE

1 x Adafruit DragonTail

Adafruit DragonTail for micro:bit - Fully Assembled (or use 3 Alligator Clip to Male Jumper Wires)

1 x 1k Resistor

Through-Hole Resistors - 1.0K ohm 5% 1/4W - Pack of 25 (1 needed)

Circuit Playground Bluefruit with TFT Gizmo version

Add to Cart

Out of

Stock

Out of

Stock

1 x Circuit Playground Bluefruit (CPB)

Circuit Playground Bluefruit - Bluetooth Low Energy

1 x Circuit Playground TFT Gizmo (LCD Screen)

Circuit Playground TFT Gizmo - Bolt-on Display + Audio Amplifier

2 x STEMMA 3-Pin to Male Header Cable

STEMMA JST PH 3-Pin to Male Header Cable - 200mm

Circuit Playground Bluefruit only version

1 x Circuit Playground Bluefruit (CPB)

Circuit Playground Bluefruit - Bluetooth Low Energy

1 x 1k Resistor

Through-Hole Resistors - 1.0K ohm 5% 1/4W - Pack of 25 (1 needed)

Common

1 x USB 1m cable - A to Micro-B

USB cable - USB A to Micro-B - 3 foot long

1 x Half-size breadboard

Half-size breadboard

1 x Alligator Clip to Male Jumper Wires

Small Alligator Clip to Male Jumper Wire Bundle - 6 Pieces (2 needed for coil)

1 x Male/Male Jumper Wires

Premium Male/Male Jumper Wires - 40 x 3" (75mm)

1 x Signal Diode

1N4148 Signal Diode - 10 pack (1 needed)

1 x 0.1uF Capacitor

0.1uF ceramic capacitors - 10 pack (1 needed)

1 x 36ft (11m) Wire

Enameled Copper Magnet Wire – 11 meters / 0.1mm diameter (5-8m of most insulated wire will work fine)

Add to Cart

Out of

Stock

Add to Cart

Out of

Stock

Add to Cart

Out of

Stock

Add to Cart

1 x 3 x AAA Switched Battery Holder

3 x AAA Battery Holder with On/Off Switch and 2-Pin JST (if you want to be mobile!)

1 x AAA Batteries

Pack of 3

Add to Cart

Design

Inductance is a key part of many technologies in daily life, for example:

charging - electric toothbrushes, the latest smartphones and some wireless, in-ear headphones;

heating - induction cooking (https://adafru.it/L7e) with metal cookware;

communication - contactless smartcards using NFC (https://adafru.it/L7f), RFID (https://adafru.it/L7A)

tags and traditional tuning circuits for radios;

power supplies - transformers (https://adafru.it/L7B) reduce the mains AC voltage to a more practical

level;

metal detection - airport security, automatic car park exit gates, pipe/cable finders and hunting for

treasure.

Leon Theremin's The Thing (https://adafru.it/L7C) is an interesting, minimalist example of a resonant cavity

microphone, the equivalent of using an inductor for L (https://adafru.it/L7D)C (https://adafru.it/L7E) tuning,

an application of band-pass filtering (https://adafru.it/L7F).

Inductance and Permeability

A current flowing produces a magnetic field around it. Inductors are electrical components designed to

store energy in that magnetic field. These are typically coils and often wrapped around a core. The

magnetic field can be affected by:

the material it passes through, this property is referred to as magnetic

permeability; (https://adafru.it/L8a)

the presence of a conductor nearby changing the effective inductance of the coil from the induced

eddy currents (https://adafru.it/L8b) in that conductor creating their own magnetic field;

other magnetic fields.

These first two properties make the inductor useful for detecting conductive objects.

MAKE Presents: The Inductor (https://adafru.it/L8c) is an excellent video introduction to inductors by Collin

Cunningham (https://adafru.it/L8d).

Metal Detection

The effect of nearby conductors on an inductor makes them a useful component for detecting metal. A

classic implementation of this in electronics uses heterodyning (https://adafru.it/L8e) where the beat

frequency from mixing an inductor-based search oscillator with a reference oscillator is output to

headphones.

Beat Frequency From An Oscillator Pair

The schematic on the left from R.M. Marston's

20 Solid State

Projects For The Home (1969)

shows a transitor-based

detector with two colpitts oscillators (https://adafru.it/L8f). One

oscillator uses the search coil and the other a tuneable

reference coil which the users adjust to reduce the beat

frequency audio output to near 0Hz away from the target

material.

RLC Filters

Filters can easily be created with a resistor (R), an inductor (L) and a capacitor (C). There are a variety of

configurations of RLC filters (https://adafru.it/L8A) and many of them could be used to filter the square

wave output from a microcontroller which could then be sampled to check the attenuation of the filter

which would vary with the inductance.

An initial test of this approach with an Adafruit CLUE and a low-pass filter didn't yield promising results.

The plots below show theoretical plots for a band-stop (notch) filter made with a resistor and a parallel LC

circuit which might be worth exploring.

The lower resistor values might not be practical as they put a higher current demand on the GPIO port.

The annotated linear plot below is better for seeing how this attenuation could potentially be used to

detect small variations in inductance.

This would require sampling the 989Hz signal to determine the attenuation by the filter. A high

inductance is attractive here as it will lower the frequency making the determination of the attenuation

more accurate.

A frequency sweeping approach is an alternative for finding the frequency of the filter. This is likely to be

slower but it would be less ambiguous. A simple measurement approach at one frequency, say 2.741V,

corresponds to

two

frequencies and therefore two different inductance values.

Charging a Capacitor with RLD

An Arduino-based project on Instructables (https://adafru.it/L8B) uses an RL circuit (https://adafru.it/L8C)

with the output rectified with a diode which then charges a capacitor. The steps in the measurement of

the inductance are:

1. A few pulses are output through the circuit to charge the capacitor. A higher inductance will result in

a higher final voltage across the capacitor.

2. An analogue input then measures the capacitor's voltage with over-sampling aiming to improve the

accuracy.

3. The analogue input is changed momentarily to

output mode

to empty (sink (https://adafru.it/L8D)) the

charge from the capacitor.

A C++ program (sketch) on the Arduino Uno offers precise timing. This is essential for this approach to

give accurate results for the inductance.

In CircuitPython, the pulseio library (https://adafru.it/L8E) can be used for creating PWM signals and pulse

trains with microsecond precision. In general, as an interpreted language with garbage collection, it does

not offer precise timing. The unpredictable delay between step 1 and step 2 is likely to affect the final

accuracy of the measurement causing sporadic, spurious indications.

Continuous Charge/Discharge with RLD

The previous approach can be used in a continuous fashion where a constant series of pulses flow

through the RLD. A circuit diagram from the Falstad Circuit Simulator (https://adafru.it/L8F) is shown below.

This design could be considered as an RL filter with an envelope detector (https://adafru.it/L9a).

The value of the capacitor affects how quickly it discharges. A

tiny capacitance will cause a rapid discharge causing a ripple

which may reduce the accuracy or complicate the voltage

measurement. A large capacitor value will take time to charge

and discharge and this could make the sensing unresponsive.

A value of 0.1uF (which can be written as 100nF) was chosen

from experimental testing. For comparison, a simulation with

100pF (top left) shows a very undesirable 197mV of ripple

whereas 0.1uF only has ~1mV ripple.

A small amount of steady voltage drop around 1mV is actually useful here to ensure over-sampling is an

effective technique to improve the resolution. In the (unlikely) absence of noise or variation, a

theoretically

perfect

analogue to digital converter (ADC) (https://adafru.it/eYp) would output the same value repeatedly

for a constant voltage. The ADC Analysis (https://adafru.it/L9b) page takes a closer look at this.

Two Coil Systems

Modern metal detectors using the induction balanced approach use two, often partially overlapping

search coils. One is used for transmitting and one for receiving. A relatively small overlap will create a

section with increased sensitivity. These detectors can discriminate to some extent between metals by

reporting on the phase difference (https://adafru.it/L9c) between the transmitted and received signal. This

is typically presented to the user as a numerical value with different ranges giving an approximate

identification. Garrett's chart for their AT Pro metal detector is shown below.

CLUE Metal Detector

Some initial testing of the Continuous Charge/Discharge with RLD approach worked well so this was

selected for the project.

The CLUE has an onboard LIS3MDL, a triple-axis magnetometer. This is a useful addition for finding

magnets and magnetised items.

Microcontrollers vs Inductors

Inductors can generate high voltages which may exceed the desired levels in a circuit. The video above

shows a single-cell battery connected to an inductor (top right) in series with three white LEDs. The white

LEDs require over 9V to illuminate but a mere 1.5V battery is able to briefly illuminate them due to the

inductor's effect.

In this case the red wire is being used to briefly short across the non-conducting LEDs to allow current to

flow from the battery through the inductor. The inductor is storing energy in its magnetic field and this field

products the momentary higher voltage as the red wire is removed from the circuit. This demonstration of

voltage spikes suggests care is required when using inductors in circuits to keep voltage levels at normal

levels to avoid damaging sensitive components.

TDK (https://adafru.it/Lb1), a company founded on the invention of ferrite (https://adafru.it/Lb2), offers an

explanation of this below with a parallel version of the circuit lighting a 70V neon

lamp (https://adafru.it/Lb3) from a 4.5V battery. This is from TDK's The Wonders of Electromagnetism:

Power Inductors in Mobile Phones (https://adafru.it/Lb4).

GPIO Protection

The general-purpose input/output (GPIO) (https://adafru.it/Lb5) pins on microcontrollers typically have

some limited protection built-in for adverse voltages often to deal with static electricity

(ESD (https://adafru.it/Lb6)). The CLUE board uses an nRF52 series chip and this has two internal

diodes (https://adafru.it/Lb7) on each GPIO pin. The partial schematic below shows an example of how

these these two diodes are used for one pin.

The schematic shows the CLUE board's 1 Megaohm resistor. There's one resistor per large pad used for

the capacitive touch (https://adafru.it/Lb8) implementation. The schematic also shows an

external

resistor.

This is another precaution that's typically used to limit output current but it will also reduce any current

flowing through these

very small

, protective diodes in the microcontroller.

The metal detector circuit on the next page uses a resistor

primarily to limit the current from the P1

output

but it will also

reduce any adverse currents from under or over voltages

caused by the inductor.

The square wave (3.3V pk-pk (https://adafru.it/oDb), 84% duty

cycle (https://adafru.it/Lb9)) can be seen with and without the

inductor in the circuit here. The inductor does cause a small

negative

voltage which briefly "peaks" at -0.6V on the P1

pin/pad. The magnitude and brevity of this spike and the

current protection from the external 1k resistor mean the

microcontroller is not at risk.

Larger Coil Currents

If more current was being used through the coil then an external protection diode capable of handling this

higher current would be a wise precaution. The CLUE's nRF52840 can only supply low currents, higher

currents would need a separate power supply and switching with a transistor. This could aid isolation of

the GPIO from the maleffects of the voltage spikes.

Diodes are commonly found across motors (https://adafru.it/CkQ), relays and solonoids protecting against

back EMF (https://adafru.it/Lba) and are sometimes referred to as "flyback" diodes (https://adafru.it/Lbb).

Circuit

This page describes how the components are used on the breadboard to make the circuit for the metal

detector. It also describes how to make and connect the coil.

Components

The components in the circuit are:

R1 - 1k resistor.

D2 - 1N4148 signal diode (there is no D1).

C1 - 0.1uF (100nF) ceramic capacitor. These small capacitors are often labelled "104".

L1 - home-made coil.

The prototype was made with a 1N4004 rectifier diode and also tested with a germanium diode from a

crystal radio set, both worked well and could be used as alternatives to the 1N4148 diode.

Coil Construction

A coil with about 4-8m (13-26ft) is a good starting point to avoid using too much wire. Insulated wire will

work but "enamelled" copper wire (https://adafru.it/Lbc) allows a more compact coil. The enamel is a

misnomer, the coating will be something like polyurethane varnish. This insulation must be

scraped

or

burnt off

with a soldering iron at the ends to expose the copper to connect it to the circuit.

The coil shown at the top of the page is enamelled 0.56mm wire wrapped around an 84mm tube (3.3in). It

has 12 coils then 9 more coils over those then 7 coil more coils over those totalling 28. Placing the coils

close to the edge improves the effective search range but care needs to be taken to ensure the coil does

not fall off! A tiny ridge has been made on end of the tube with masking tape to reduce that risk.

The coil either needs to be very tight or held in place as movement of the wire in the coil will subtly affect

the inductance and parasitic capacitance (https://adafru.it/Lbd) of the coil.

A prototype coil was also made (not shown) with 20 turns around a core of a roll of masking tape with

diameter 116mm (4.6in). This worked well too.

Circuit Construction

The diagrams and pictures below show how the circuit can be implemented on a breadboard for the three

different configurations.

CLUE board

The coil needs to be connected to the breadboard. The options are:

Thick solid core wire may be directly inserted into the breadboard. Tinning the end with solder will

increase the diameter of a wire and tame multi-strand wire.

A connector cable with male pins to alligator (crocodile) clips or hooks (shown below). These will be

needed for the Adafruit enamelled wire.

The CLUE board can be connected using the Dragontail or alligator clips.

#0 (P0) yellow wire - this is the square wave output.

#1 (P1) green wire - this is an analogue input measuring the voltage across the capacitor.

GND black wire - this is only required if not using the Dragontail. The Dragontail directly connects to

the power rails on

one

side of the breadboard.

 It's best to insert or remove a CLUE board from an edge connector with the power off to prevent

inadvertent, transient short circuits.

Everything can be seen connected together in the picture below. A Kitronik Edge Connector Breakout

Board for BBC micro:bit (https://adafru.it/Lbe) (over the top half of the breadboard) and Pimoroni IC hooks

with pigtails (https://adafru.it/Lbf) (to connect the coil) have been used for this implementation.

The circuit can only be tested once the CLUE has the CircuitPython program on it. This is described on

the next page.

 If alligator clips are used they need to be carefully placed in the centre of the pad and protected

from accidental nudges which could cause the alligator clip to connect across the small pads either

side of #0, #1 or GND.

Circuit Playground Bluefruit with TFT Gizmo

The CPB board pads are not really accessible when the TFT Gizmo is attached and most of them are used

for the Gizmo. The Gizmo has 3-pin STEMMA connectors for accessing A1 and A2. A pair of STEMMA 3-

Pin to male cables (https://adafru.it/CVg) are required to connect this to the breadboard.

The connections are:

A1 STEMMA (square wave output):

red - breadboard red (+) rail (not used).

white (yellow sleeves) - breadboard b22.

black - breadboard black (-) rail.

A2 STEMMA (analogue input):

red - breadboard red (+) rail (not used).

white (green sleeves) - breadboard e26.

black - breadboard black (-) rail.

The TFT Gizmo has its own 1k resistors on the A1/A2 GPIO making the resistor on the breadboard

superfluous.

The red power lines are not used but plugging the pins into the breadboard prevents them from

accidentally contacting other components or shorting to ground.

 The red power lines from the STEMMA connector on the TFT Gizmo are at VOUT level, i.e. 5V for

USB power or the battery voltage.

Circuit Playground Bluefruit board only

The program still runs without a screen on a CPB board in audio/light mode.

The connections are:

A1 (square wave output) - yellow wire - breadboard a18.

A2 (analogue input) - green wire - breadboard e26.

GND - black wire - breadboard black (-) rail.

CircuitPython on CLUE

CircuitPython (https://adafru.it/tB7) is a derivative of MicroPython (https://adafru.it/BeZ) designed to

simplify experimentation and education on low-cost microcontrollers. It makes it easier than ever to get

prototyping by requiring no upfront desktop software downloads. Simply copy and edit files on the

CIRCUITPY flash drive to iterate.

The following instructions will show you how to install CircuitPython. If you've already installed

CircuitPython but are looking to update it or reinstall it, the same steps work for that as well!

Set up CircuitPython Quick Start!

Follow this quick step-by-step for super-fast Python power :)

https://adafru.it/IHF

Click the link above to download the latest version of

CircuitPython for the CLUE.

Download and save it to your desktop (or wherever is handy).

Plug your CLUE into your computer using a known-good USB

cable.

A lot of people end up using charge-only USB cables and it

is very frustrating! So make sure you have a USB cable you

know is good for data sync.

Double-click the Reset button on the top (magenta arrow) on

your board, and you will see the NeoPixel RGB LED (green

arrow) turn green. If it turns red, check the USB cable, try

another USB port, etc. Note: The little red LED next to the

USB connector will pulse red. That's ok!

If double-clicking doesn't work the first time, try again.

Sometimes it can take a few tries to get the rhythm right!

https://adafru.it/IHF

You will see a new disk drive appear called CLUEBOOT.

Drag the adafruit-circuitpython-clue-etc.uf2 file to

CLUEBOOT.

The LED will flash. Then, the CLUEBOOT drive will disappear

and a new disk drive called CIRCUITPY will appear.

If this is the first time you're installing CircuitPython or you're

doing a completely fresh install after erasing the filesystem,

you will have two files - boot_out.txt, and code.py, and one

folder - lib on your CIRCUITPY drive.

If CircuitPython was already installed, the files present before

reloading CircuitPython should still be present on your

CIRCUITPY drive. Loading CircuitPython will not create new

files if there was already a CircuitPython filesystem present.

That's it, you're done! :)

CircuitPython on Circuit Playground Bluefruit Install or Update CircuitPython

Follow this quick step-by-step to install or update CircuitPython on your Circuit Playground Bluefruit.

https://adafru.it/FNK

Click the link above and download the latest UF2 file

Download and save it to your Desktop (or wherever is handy)

Plug your Circuit Playground Bluefruit into your computer

using a known-good data-capable USB cable.

A lot of people end up using charge-only USB cables and it

is very frustrating! So make sure you have a USB cable you

know is good for data sync.

Double-click the small Reset button in the middle of the CPB

(indicated by the red arrow in the image). The ten NeoPixel

LEDs will all turn red, and then will all turn green. If they turn

all red and stay red, check the USB cable, try another USB

port, etc. The little red LED next to the USB connector will

pulse red - this is ok!

If double-clicking doesn't work the first time, try again.

Sometimes it can take a few tries to get the rhythm right!

(If double-clicking doesn't do it, try a single-click!)

https://adafru.it/FNK

You will see a new disk drive appear called CPLAYBTBOOT.

Drag the adafruit_circuitpython_etc.uf2 file to

CPLAYBTBOOT.

The LEDs will turn red. Then, the CPLAYBTBOOT drive will

disappear and a new disk drive called CIRCUITPY will

appear.

That's it, you're done! :)

CircuitPython

Libraries

Once you've gotten CircuitPython onto your CLUE or Circuit Playground Bluefruit (CPB) board, it's time to

add some libraries. You can follow this guide page (https://adafru.it/GdM) for the basics of downloading

and transferring libraries to the board.

https://adafru.it/ENC

Libraries for Metal Detector for CLUE

From the library bundle you downloaded in that guide page, transfer the following libraries onto the CLUE

board's /lib directory:

adafruit_apds9960

adafruit_bus_device

adafruit_display_notification

adafruit_display_text

adafruit_register

adafruit_display_shapes

adafruit_bmp280.mpy

adafruit_clue.mpy

adafruit_lis3mdl.mpy

adafruit_lsm6ds.mpy

adafruit_sht31d.mpy

adafruit_slideshow.mpy

neopixel.mpy

There are many libraries with similar names, take care on the selection.

Libraries for Metal Detector for Circuit Playground Bluefruit with TFT Gizmo

From the library bundle you downloaded in that guide page, transfer the following libraries onto the CPB

board's /lib directory:

adafruit_gizmo

adafruit_circuitplayground

adafruit_display_shapes

adafruit_bus_device

adafruit_display_notification

adafruit_display_text

adafruit_register

adafruit_lis3dh.mpy

adafruit_thermistor.mpy

adafruit_st7789.mpy

neopixel.mpy

Development Testing

During development, the application was tested on a CLUE using CircuitPython 5.2.0 with libraries from

the adafruit-circuitpython-bundle-5.x-mpy-20200501.zip bundle. It should work on subsequent versions,

https://adafru.it/ENC

the latest version is recommended for the CLUE (https://adafru.it/IHF).

A small amount of testing was also performed on a Circuit Playground Bluefruit (https://adafru.it/FNK) with

a TFT Gizmo.

Metal Detector

Download the CircuitPython file below renaming the clue-metal-detector.py to code.py by clicking on the

links and then using Save as... / Save link as... in the browser. The files are hosted on Adafruit's GitHub

repo for this project (https://adafru.it/L9d).

https://adafru.it/L9e

Plug your CLUE/CPB board into your computer via a known-good USB data cable. A flash drive named

CIRCUITPY should appear in your file explorer/finder program. Copy the file t o the CIRCUITPY drive

ensuring the clue-metal-detector.py is renamed to code.py. (https://adafru.it/EL3)

Example Video

The video shows the CLUE version powered by a lithium polymer battery similar to the Adafruit 1200mAh

Lithium Ion Polymer battery (https://adafru.it/dyW). Note: the CLUE and the CPB do not have an integrated

charger.

In the video, when no object is being sensed, the voltage shown on the screen is around 1474mV and

magnitude of the magnetic flux density difference is 0uT. The five hidden objects, in order, show the

following voltages:

Through a large hardback book

a large metallic sticker, 1467mV.

Through a magazine

another Adafruit CLUE board, 1463mV;

a ferrite core from an inductor, 1477mV (note the value has

increased

);

a neodymium magnet, 1474mV and 28uT;

a large silver coin 1469mV.

https://adafru.it/L9e

The voltage will vary based on the inductance of the coil created for the metal detector. It will be about

300mV less if a rectifier diode like a 1N1004 is used. The voltage is about 200mV less on the Circuit

Playground Bluefruit with TFT Gizmo for the same coil.

Troubleshooting

If the metal detector is not working, here's some tips based on observing the voltage.

Around 2950mV: the coil is not connected or the connection is hampered by insulation left on the

enamelled wire.

Around 0mV: diode may be the wrong way around or something is not connected properly.

A few tens of mV: the yellow connection is probably from a high (3.3V) pin.

Voltage jumps around: probably a loose connection and/or ground is not attached. Wiggle and re-

insert connections to find problematic one. Using alternate holes/rows on the breadboard can help

sometimes.

Operation

The mV value across the capacitor is shown on screen. This value represents the inductance value. The

detection of metal is based on a positive or negative

change

from the baseline value when no object is

being sensed. A difference is indicated by a beeping sound, a bar graph with green for positive and red

for negative and flashing of the NeoPixel(s) with a matching colour. The baseline value is assigned when

the code first starts. It will also follow any changes after about ten seconds.

The uT reading (CLUE board only) is the magnitude of the difference between the magnetometer's z

component only and the first value measured at start-up. This value is also shown as a filled blue circle, a

slightly different beeping sound and flashing of the NeoPixel(s) in blue alternating with any mV related

colour.

The use of the z component only is a crude approach to make the detector ignore the Earth's magnetic

field. This allows the detector to be rotated as this changes the x and y values but not the z value. Tilting

the device, as seen in the video when the metal detector is at the top of the screen, will unfortunately

increase the value slightly.

The right button can be used to immediately reset the baseline for the voltage and the magnetic flux

density. The left button toggles the audio, NeoPixel(s), screen and Mu output on and off depending on the

duration of the button press.

 Magnets at close proximity can permanently magnetise components on the CLUE board affecting

the magnetometer! Keep them at least 10cm (4in) away from the CLUE.

Code

A code discussion (https://adafru.it/L9f) follows the code.

# clue-metal-detector v1.6 # A simple metal detector using a minimum number of external components

# Tested with an Adafruit CLUE (Alpha) and CircuitPython 5.2.0 # Tested with an Adafruit Circuit Playground Bluefruit with TFT Gizmo # and CircuitPython 5.2.0

# CLUE: Pad P0 is an output and pad P1 is an input # CPB: Pad/STEMMA A1 is an output and Pad/STEMMA A2 is an input

# copy this file to CLUE/CPB board as code.py

# MIT License

# Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software.

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# pylint: disable=global-statement

import time import math import array import os import gc

import board import pulseio import analogio import ulab

from displayio import Group import terminalio

# These imports works on CLUE, CPB (and CPX on 5.x) from audiocore import RawSample try: from audioio import AudioOut except ImportError: from audiopwmio import PWMAudioOut as AudioOut

# displayio graphical objects from adafruit_display_text.label import Label from adafruit_display_shapes.rect import Rect from adafruit_display_shapes.circle import Circle

# Assuming CLUE if it's not a Circuit Playround (Bluefruit) clue_less = "Circuit Playground" in os.uname().machine

if clue_less: # CPB with TFT Gizmo (240x240) from adafruit_circuitplayground import cp from adafruit_gizmo import tft_gizmo

# Outputs display = tft_gizmo.TFT_Gizmo() audio_out = AudioOut(board.SPEAKER) min_audio_frequency = 100 max_audio_frequency = 4000 pixels = cp.pixels board_pin_output = board.A1

# Enable the onboard amplifier for speaker cp._speaker_enable.value = True # pylint: disable=protected-access

# Inputs board_pin_input = board.A2 magnetometer = None # This indicates device is not present button_left = lambda: cp.button_b button_right = lambda: cp.button_a

else: # CLUE with builtin screen (240x240) from adafruit_clue import clue

# Outputs display = board.DISPLAY audio_out = AudioOut(board.SPEAKER) min_audio_frequency = 100 max_audio_frequency = 5000 pixels = clue.pixel board_pin_output = board.P0

# Inputs (buttons reversed as it is used upside-down with Gizmo) board_pin_input = board.P1 magnetometer = lambda: clue.magnetic button_left = lambda: clue.button_a button_right = lambda: clue.button_b

# Globals variables used r/w in functions last_frequency = 0 last_negbar_len = None last_posbar_len = None last_mag_radius = None text_overlay_gob = None voltage_barneg_dob = None voltage_sep_dob = None voltage_barpos_dob = None magnet_circ_dob = None

# Globals debug = 1 screen_height = display.height screen_width = display.width samples = []

# Other globals quantize_tones = True audio_on = True screen_on = True mu_output = False neopixel_on = True

# Used to alternate/flash the NeoPixel neopixel_alternate = True

# Some constants used in start_beep() BASE_NOTE = 261.6256 # C4 (middle C) QUANTIZE = 4 # determines the "scale" POSTLOG_FACTOR = QUANTIZE / math.log(2)

AUDIO_MIDPOINT = 32768

# There's room for 80 pixels but 60 draws a bit quicker VOLTAGE_BAR_WIDTH = 60 VOLTAGE_BAR_HEIGHT = 118 VOLTAGE_BAR_SEP_HEIGHT = 4 MAG_MAX_RADIUS = 50

VOLTAGE_FMT = "{:6.1f}" MAG_FMT = "{:6.1f}"

INFO_FG_COLOR = 0x000080 INFO_BG_COLOR = 0xc0c000 BLACK_TUPLE = (0, 0, 0)

RED = 0xff0000 GREEN75 = 0x00c000 BLUE = 0x0000ff WHITE75 = 0xc0c0c0

FONT_WIDTH, FONT_HEIGHT = terminalio.FONT.get_bounding_box()

# Thresholds below which audio is silent and NeoPixels are dark threshold_voltage = 0.002 threshold_mag = 2.5

def d_print(level, *args, **kwargs): """A simple conditional print for debugging based on global debug level.""" if not isinstance(level, int): print(level, *args, **kwargs) elif debug >= level: print(*args, **kwargs)

# Adapted and borrowed from clue-plotter v1.14 def wait_release(text_func, button_func, menu): """Calls button_func repeatedly waiting for it to return a false value and goes through menu list as time passes.

The menu is a list of menu entries where each entry is a two element list of time passed in seconds and text to display for that period. Text is displayed by calling text_func(text). The entries must be in ascending time order."""

start_t_ns = time.monotonic_ns() menu_option = None selected = False

for menu_option, menu_entry in enumerate(menu): menu_time_ns = start_t_ns + int(menu_entry[0] * 1e9) menu_text = menu_entry[1] if menu_text: text_func(menu_text) while time.monotonic_ns() < menu_time_ns: if not button_func(): selected = True

break if menu_text: text_func("") if selected: break

return (menu_option, (time.monotonic_ns() - start_t_ns) * 1e-9)

def popup_text(text_func, text, duration=1.0): """Place some text on the screen using info property of Plotter object for duration seconds.""" text_func(text) time.sleep(duration) text_func(None)

def show_text(text): """Place text on the screen. Empty string or None clears it.""" global screen_group, text_overlay_gob

if text: font_scale = 3 line_spacing = 1.25

text_lines = text.split("\n") max_word_chars = max([len(word) for word in text_lines]) # If too large reduce the scale to 2 and hope! if (max_word_chars * font_scale * FONT_WIDTH > screen_width or (len(text_lines) * font_scale * FONT_HEIGHT * line_spacing) > screen_height): font_scale -= 1

text_overlay_gob = Label(terminalio.FONT, text=text, scale=font_scale, background_color=INFO_FG_COLOR, color=INFO_BG_COLOR) # Centre the (left justified) text text_overlay_gob.x = (screen_width

- font_scale * FONT_WIDTH * max_word_chars) // 2 text_overlay_gob.y = screen_height // 2 screen_group.append(text_overlay_gob) else: if text_overlay_gob is not None: screen_group.remove(text_overlay_gob) text_overlay_gob = None

def voltage_bar_set(volt_diff): """Draw a bar based on positive or negative values. Width of 60 is performance compromise as more pixels take longer.""" global voltage_sep_dob, voltage_barpos_dob, voltage_barneg_dob global last_negbar_len, last_posbar_len

if voltage_sep_dob is None: voltage_sep_dob = Rect(160, VOLTAGE_BAR_HEIGHT, VOLTAGE_BAR_WIDTH, VOLTAGE_BAR_SEP_HEIGHT, fill=WHITE75) screen_group.append(voltage_sep_dob)

if volt_diff < 0: negbar_len = max(min(-round(volt_diff * 5e3),

VOLTAGE_BAR_HEIGHT), 1) posbar_len = 1 else: negbar_len = 1 posbar_len = max(min(round(volt_diff * 5e3), VOLTAGE_BAR_HEIGHT), 1)

if posbar_len == last_posbar_len and negbar_len == last_negbar_len: return

if voltage_barpos_dob is not None: screen_group.remove(voltage_barpos_dob) if posbar_len > 0: voltage_barpos_dob = Rect(160, VOLTAGE_BAR_HEIGHT - posbar_len, VOLTAGE_BAR_WIDTH, posbar_len, fill=GREEN75) screen_group.append(voltage_barpos_dob) last_posbar_len = posbar_len

if voltage_barneg_dob is not None: screen_group.remove(voltage_barneg_dob) if negbar_len > 0: voltage_barneg_dob = Rect(160, VOLTAGE_BAR_HEIGHT + VOLTAGE_BAR_SEP_HEIGHT, VOLTAGE_BAR_WIDTH, negbar_len, fill=RED) screen_group.append(voltage_barneg_dob) last_negbar_len = negbar_len

def magnet_circ_set(mag_ut): """Display a filled circle to represent the magnetic value mag_ut in microteslas.""" global magnet_circ_dob global last_mag_radius

# map microteslas to a radius with minimum of 1 and # maximum of MAG_MAX_RADIUS radius = min(max(round(math.sqrt(mag_ut) * 4), 1), MAG_MAX_RADIUS)

if radius == last_mag_radius: return

if magnet_circ_dob is not None: screen_group.remove(magnet_circ_dob) magnet_circ_dob = Circle(60, 180, radius, fill=BLUE) screen_group.append(magnet_circ_dob)

def manual_screen_refresh(disp): """Refresh the screen as immediately as is currently possibly with refresh method.""" refreshed = False while True: try: # 1000fps is fastest library allows - this high value # minimises any delays this refresh() method introduces refreshed = disp.refresh(minimum_frames_per_second=0, target_frames_per_second=1000) except RuntimeError: pass if refreshed: break

def neopixel_set(pix, d_volt, mag_ut): """Set all the NeoPixels to an alternating colour based on voltage difference and magnitude of magnetic flux density difference.""" global neopixel_alternate

np_r, np_g, np_b = BLACK_TUPLE if neopixel_alternate: # RGB values are 8bit, hence the cap of 255 using min() if abs(d_volt) > threshold_voltage: if d_volt < 0.0: np_r = min(round(-d_volt * 8e3), 255) else: np_g = min(round(d_volt * 8e3), 255) else: if mag_ut > threshold_mag: np_b = min(round(mag_ut * 6), 255)

pix.fill((np_r, np_g, np_b)) # Note: double brackets to pass tuple neopixel_alternate = not neopixel_alternate

def start_beep(freq, wave, wave_idx): """Start playing a continous beep based on freq and waveform specified by wave_idx. A frequency of 0 will stop the note playing. This quantizes the notes into a scale to make beeping sound more pleasant. This modifies the sample_rate property of the RawSample objects. """ global last_frequency if freq == 0: if last_frequency != 0: audio_out.stop() last_frequency = 0 return

if quantize_tones: note_freq = BASE_NOTE * 2**((round(math.log(freq / BASE_NOTE) * POSTLOG_FACTOR)) / QUANTIZE) d_print(3, "Quantize", freq, note_freq) else: note_freq = freq

(waveform, wave_samples_n) = wave[wave_idx] new_freq = round(note_freq * wave_samples_n) # Only set the new frequency if it's not the same as last one if new_freq != last_frequency: waveform.sample_rate = new_freq audio_out.play(waveform, loop=True) last_frequency = new_freq

def make_sample_list(levels=10, volume=32767, range_l=24, start_l=8): """Make a list of tuples of (RawSample, sample_length) with a sine wave of varying resolution from high to low. The lower resolutions sound crunchier and louder on the CLUE."""

# Make a range of sample lengths, default is between 32 and 8 sample_lens = [int((x*(range_l + .99)/(levels - 1)) + start_l) for x in range(0, levels)] sample_lens.reverse()

wavefs = [] for s_len in sample_lens: raw_samples = array.array("H", [round(volume * math.sin(2 * math.pi * (idx / s_len))) + AUDIO_MIDPOINT for idx in range(s_len)]) sound_samples = RawSample(raw_samples) wavefs.append((sound_samples, s_len))

return wavefs

waveforms = make_sample_list()

# For testing the waveforms if debug >= 4: for idx in range(len(waveforms)): start_beep(440, waveforms, idx) time.sleep(0.1) start_beep(0, waveforms, 0) # This silences it

# See https://forums.adafruit.com/viewtopic.php?f=60&t=164758 for # a comparison and performance analysis of alternate techniques for this def sample_sum(pin, num): """Sample the analogue value from pin num times and return the sum of the values.""" global samples # Not strictly needed - indicative of r/w use samples[:] = [pin.value for _ in range(num)] return sum(samples)

# Initialise detector display # The units are created as separate text objects as they are static # and this reduces the amount of redrawing for the dynamic numbers FONT_SCALE = 3

if magnetometer is not None: magnet_value_dob = Label(font=terminalio.FONT, text="----.-", scale=FONT_SCALE, color=0xc0c000) magnet_value_dob.y = 90

magnet_units_dob = Label(font=terminalio.FONT, text="uT", scale=FONT_SCALE, color=0xc0c000) magnet_units_dob.x = len(magnet_value_dob.text) * FONT_WIDTH * FONT_SCALE magnet_units_dob.y = magnet_value_dob.y

voltage_value_dob = Label(font=terminalio.FONT, text="----.-", scale=FONT_SCALE, color=0x00c0c0) voltage_value_dob.y = 30

voltage_units_dob = Label(font=terminalio.FONT, text="mV", scale=FONT_SCALE, color=0x00c0c0) voltage_units_dob.y = voltage_value_dob.y

voltage_units_dob.x = len(voltage_value_dob.text) * FONT_WIDTH * FONT_SCALE

# 9 elements, 4 added immediately, 4 later, 1 spare for on-screen text screen_group = Group(max_size=4 + 4 + 1) if magnetometer is not None: screen_group.append(magnet_value_dob) screen_group.append(magnet_units_dob) screen_group.append(voltage_value_dob) screen_group.append(voltage_units_dob)

# Initialise some displayio objects and append them # The following four variables are set by these two functions # voltage_barneg_dob, voltage_sep_dob, voltage_barpos_dob # magnet_circ_dob voltage_bar_set(0) if magnetometer is not None: magnet_circ_set(0)

# Start-up splash screen display.show(screen_group)

# Start-up splash screen popup_text(show_text, "\n".join(["Button Guide", "Left: audio", " 2secs: NeoPixel", " 4s: screen", " 6s: Mu output", "Right: recalibrate"]), duration=10)

# P1 or A2 for analogue input pin_input = analogio.AnalogIn(board_pin_input) CONV_FACTOR = pin_input.reference_voltage / 65535

# Start pwm output on P0 or A1 # 400kHz and 55000 (84%) duty_cycle were chosen empirically to maximise # the voltage and the voltage drop detecting a small pair of metal scissors pwm = pulseio.PWMOut(board_pin_output, frequency=400 * 1000, duty_cycle=0, variable_frequency=True) pwm.duty_cycle = 55000

# Get a baseline value for magnetometer totals = [0.0] * 3 mag_samples_n = 10 if magnetometer is not None: for _ in range(mag_samples_n): mx, my, mz = magnetometer() totals[0] += mx totals[1] += my totals[2] += mz time.sleep(0.05)

base_mx = totals[0] / mag_samples_n base_my = totals[1] / mag_samples_n base_mz = totals[2] / mag_samples_n

# Wait a bit for P1/A2 input to stabilise _ = sample_sum(pin_input, 3000) / 3000 * CONV_FACTOR base_voltage = sample_sum(pin_input, 1000) / 1000 * CONV_FACTOR voltage_value_dob.text = "{:6.1f}".format(base_voltage * 1000.0)

# Auto refresh off

display.auto_refresh = False

# Store two previous values of voltage to make a simple # filtered value voltage_zm1 = None voltage_zm2 = None filt_voltage = None

# Initialise the magnitude of the # magnetic flux density difference from its baseline mag_mag = 0.0

# Keep some historical voltage data to calculate median for re-baselining # aiming for about 10 reads per second so this gives # 20 seconds voltage_hist = ulab.zeros(20 * 10 + 1, dtype=ulab.float) voltage_hist_idx = 0 voltage_hist_complete = False voltage_hist_median = None

# Reduce the frequency of the more heavyweight graphical changes update_basic_graphics_period = 2 update_complex_graphics_period = 4 update_median_period = 5

counter = 0 while True: # Garbage collect now to reduce likelihood it occurs # during sample reading gc.collect() if debug >=2: d_print(2, "mem_free=" + str(gc.mem_free()))

screen_updates = 0 # Used to determine if the screen needs a refresh

# Take arithmetic mean of 500 samples but take a few more samples # if the loop isn't doing other work samples_to_read = 500 # About 23ms worth on CLUE update_basic_graphics = (screen_on and counter % update_basic_graphics_period == 0) if not update_basic_graphics: samples_to_read += 150 update_complex_graphics = (screen_on and counter % update_complex_graphics_period == 0) if not update_complex_graphics: samples_to_read += 400 update_median = counter % update_median_period == 0 if not update_median: samples_to_read += 50 # Read the analogue values from P1/A2 sample_start_time_ns = time.monotonic_ns() voltage = (sample_sum(pin_input, samples_to_read) / samples_to_read * CONV_FACTOR)

# Store the previous two voltage values voltage_zm2 = voltage_zm1 voltage_zm1 = voltage

if voltage_zm1 is None: voltage_zm1 = voltage if voltage_zm2 is None: voltage_zm2 = voltage

filt_voltage = (voltage * 0.4 + voltage_zm1 * 0.3 + voltage_zm2 * 0.3)

update_basic_graphics = counter % update_basic_graphics_period == 0 update_complex_graphics = counter % update_complex_graphics_period == 0

# Update text if update_basic_graphics: voltage_value_dob.text = VOLTAGE_FMT.format(filt_voltage * 1000.0) screen_updates += 1

# Read magnetometer if magnetometer is not None: mx, my, mz = magnetometer() diff_x = mx - base_mx diff_y = my - base_my diff_z = mz - base_mz # Use the z value as a crude measure as this is # constant if the device is rotated and kept level mag_mag = math.sqrt(diff_z * diff_z) else: mag_mag = 0.0

# Calculate a new audio frequency based on the absolute difference # in voltage being read - turn small voltages into 0 for silence # between 100Hz (won't be audible) # and 5000 (loud on CLUE's miniscule speaker) diff_v = filt_voltage - base_voltage abs_diff_v = abs(diff_v) if audio_on: if abs_diff_v > threshold_voltage or mag_mag > threshold_mag: frequency = min(min_audio_frequency + abs_diff_v * 5e5, max_audio_frequency) else: frequency = 0 # silence start_beep(frequency, waveforms, min(int(mag_mag / 2), len(waveforms) - 1))

# Update the NeoPixel(s) if enabled if neopixel_on: neopixel_set(pixels, diff_v, mag_mag)

# Update voltage bargraph if update_complex_graphics: voltage_bar_set(diff_v) screen_updates += 1

# Update the magnetometer text value and the filled circle representation if magnetometer is not None: if update_basic_graphics: magnet_value_dob.text = MAG_FMT.format(mag_mag) screen_updates += 1 if update_complex_graphics: magnet_circ_set(mag_mag) screen_updates += 1

# Update the screen with a refresh if needed if screen_updates: manual_screen_refresh(display)

# Send output to Mu in tuple format if mu_output:

print((diff_v, mag_mag))

# Check for buttons and just for this section of code turn back on # the screen auto-refresh so the menus actually appear! display.auto_refresh = True if button_left(): opt, _ = wait_release(show_text, button_left, [(2, "Audio " + ("off" if audio_on else "on")), (4, "NeoPixel " + ("off" if neopixel_on else "on")), (6, "Screen " + ("off" if screen_on else "on")), (8, "Mu output " + ("off" if mu_output else "on")) ]) if not screen_on or opt == 2: # Screen toggle screen_on = not screen_on if screen_on: display.show(screen_group) display.brightness = 1.0 else: display.show(None) display.brightness = 0.0 elif opt == 0: # Audio toggle audio_on = not audio_on if not audio_on: start_beep(0, waveforms, 0) # Silence elif opt == 1: # NeoPixel toggle neopixel_on = not neopixel_on if not neopixel_on: neopixel_set(pixels, 0.0, 0.0) else: # Mu toggle mu_output = not mu_output

# Set new baseline voltage and magnetometer on right button press if button_right(): wait_release(show_text, button_right, [(2, "Recalibrate")]) d_print(1, "Recalibrate") base_voltage = voltage voltage_hist_idx = 0 voltage_hist_complete = False voltage_hist_median = None if magnetometer is not None: base_mx, base_my, base_mz = mx, my, mz

display.auto_refresh = False

# Add the current voltage to the historical list voltage_hist[voltage_hist_idx] = voltage if voltage_hist_idx >= len(voltage_hist) - 1: voltage_hist_idx = 0 voltage_hist_complete = True else: voltage_hist_idx += 1

# Adjust the reference base_voltage to the median of historical values if voltage_hist_complete and update_median: voltage_hist_median = ulab.numerical.sort(voltage_hist)[len(voltage_hist) // 2] base_voltage = voltage_hist_median

d_print(2, counter, sample_start_time_ns / 1e9, voltage * 1000.0, mag_mag, filt_voltage * 1000.0, base_voltage, voltage_hist_median)

counter += 1

Code Discussion

The high level design is straightforward.

1. Output a square wave on a pin.

2. Store a baseline value from the other pin configured as an analogue input which is measuring the

voltage across the capacitor.

3. Store a baseline value for the z component of the magnetometer (if present).

4. Take the difference from the current analogue input and the baseline and present this value to the

user.

5. Take the magnitude of the difference from the current z component of the magnetometer and the

baseline and present this value to the user.

6. Check the two buttons for user inputs.

7. Go to step 4.

Only the buttons are used for the user interface on the CLUE. There is one spare touch capable pad but

this isn't really accessible if an edge connector is used.

Voltage from ADC Values

The ADC values are easily read in CircuitPython using an AnalogIn (https://adafru.it/Du1) object's value

property. This value ranges from 0 to 65535 (a 16bit value) regardless of the number of bits returned by

the ADC. The nRF52840 is configured in 12bit ADC mode by the CircuitPython interpreter. This means

values will always be multiples of 16.

One surprise is these values can vary even with a stable voltage source like a battery. An extreme

example from some real data for consecutive values is:

1. 25152 = 1266.5mV

2. 28848 = 1452.6mV

3. 28608 = 1440.5mV

In the case of this metal detector, a 3mV difference represents a small metallic object, but the ADC is

infrequently producing output which hugely deviates from the actual value. Even the second and third

values have a 12.1mV difference.

A common approach is to take multiple samples and then take the average (arithmetic mean) of those

values with the aim of reducing the effect of this variance. The sample_sum() function below does most of

this job, it leaves the division by num to the caller.

def sample_sum(pin, num): """Sample the analogue value from pin num times and return the sum of the values.""" global samples samples[:] = [pin.value for _ in range(num)] return sum(samples)

This is one of the most efficient ways to read multiple samples with a rate of around 21-22 thousand

samples per second (ksps) on an nRF52840. It also stores them in case further data analysis is required.

The use of global here isn't strictly required but arguably it's useful to indicate the function changes the

global list samples . The values are intentionally processed here as int and not float to improve the

performance. The use of slice assignment is an attempt. probably unsuccessful, to stop the interpreter

generating a temporary list to store all the sample values.

The performance of different approaches to reading many samples is shown in Adafruit Forums:

Analogue Sampling at high rates plus ulab (https://adafru.it/ELr).

The validity of using the average of a number of consecutive samples to accurately represent the real

voltage is examined on the next page.

Using Global Variables in Python

In Python, global (https://adafru.it/L9A) must be used inside a function (or method) to declare usage of a

variable

if assignment occurs

. This prevents Python from creating a new local variable. An example from

the program is shown below.

def magnet_circ_set(mag_ut): """Display a filled circle to represent the magnetic value mag_ut in microteslas.""" global magnet_circ_dob global last_mag_radius

radius = min(max(round(math.sqrt(mag_ut) * 4),

1), MAG_MAX_RADIUS)

if radius == last_mag_radius: return

if magnet_circ_dob is not None: screen_group.remove(magnet_circ_dob) magnet_circ_dob = Circle(60, 180, radius, fill=BLUE) screen_group.append(magnet_circ_dob)

Pylint (https://adafru.it/BI5) picks up on use of global and issues a W0603: Using the global statement (global-

statement) warning. Variables with a large scope (https://adafru.it/L9B) which are not truly constant can

make a program difficult to understand and lead to bugs - global variables (https://adafru.it/L9C) are the

most extreme version of this. In a small program they tend not to be problematic but small programs can

gradually

become much larger ones. In the above case the variables have:

a clear, specific, semi-documented purpose

and a very low probability of being used elsewhere in the code in the future.

The current code does limit the display to a single circle/value. If the program was likely to grow over time

or there was a potential need to display multiple circles/values then creating a new

class (https://adafru.it/K7A) would be an attractive option to encapsulate (https://adafru.it/K9E) this data

replacing the use of global variables.

In other languages, global variables can cause limitations or bugs from ill-considered use due to multi-

threading (https://adafru.it/L9D) or re-entrancy (https://adafru.it/L9E) issues. The evolution of

errno (https://adafru.it/L9F) is one important example of a global variable used by UNIX libraries which had

to be enhanced to support true multi-threading by conversion into a function.

Positional Arguments

The majority of programming languages use positional arguments (parameters) to functions. An example

from the code is show below with the body of the procedure not shown for brevity.

def neopixel_set(pix, d_volt, mag_ut): """Set all the NeoPixels to an alternating colour based on voltage difference and magnitude of magnetic flux density difference."""

The three values are clearly very different:

1. pix - an object for the NeoPixels, the fill() method is used on it.

2. d_volt - a difference value which may be positive or negative in

volts

.

3. mag_ut - a magnetic value in microteslas which happens to be a magnitude of a difference value so

is always non-negative.

A scientist would clearly see there are two quantities with very different units. Python traditionally didn't

have any typing that would indicate if the procedure was used with the arguments in the wrong order and

during development the numerical arguments were briefly reversed by accident. The use of keyword

(named) arguments can make this less likely to occur, particularly with functions which take a huge

number of arguments. Keyword arguments are only mandatory in Python (https://adafru.it/La0) after * in

the argument list.

CircuitPython supports type hints (PEP-484) (https://adafru.it/La1) which improves the results from static

analysis tools like pylint. This can reduce bugs in this area but will not eliminate them.

Practical Issues with displayio Graphics

Drawing items on the TFT LCD screen on these boards is a slow process compared to a modern desktop

computer. This is particularly noticeable when drawing

large

objects using the adafruit_display_shapes

library (https://adafru.it/Fiu).

The program uses a variety of techniques to try and keep the main loop executing at a reasonable and

approximately constant rate both especially when a significant object is detected.

1. The default automatic screen refresh is replaced by a manual refresh once per loop to CPU cycles

are not spent on interim, fruitless, partial screen updates.

2. The MAG_MAX_RADIUS seen in the magnet_circ_set() procedure above serves to ensure the filled

circle fits on screen. It's set slightly smaller than the screen area it occupies to reduce the

performance impact of drawing very large circles.

3. Screen objects which are slow to update are reduced in frequency with an "only every N times"

approach in the main loop.

4. The number of samples read adapts to other balance other activity in the loop to keep the execution

rate more constant.

5. Graphical objects are not updated if the screen has been turned off in the program by the user.

6. The numerical values on screen are split into two Label (https://adafru.it/IDE) objects to separate the

dynamic value and the static units ( "uT" and "mV" ).

The third, fourth and fifth optimisations are shown in an excerpt below from the main loop.

# An excerpt from main loop samples_to_read = 500 # About 23ms worth on CLUE update_basic_graphics = (screen_on and counter % update_basic_graphics_period == 0) if not update_basic_graphics: samples_to_read += 150 update_complex_graphics = (screen_on and counter % update_complex_graphics_period == 0) if not update_complex_graphics: samples_to_read += 400 update_median = counter % update_median_period == 0 if not update_median: samples_to_read += 50

This is setting three boolean (https://adafru.it/IgF) variables, update_basic_graphics ,

update_complex_graphics and update_median , which are used to selectively execute certain

computationally expensive parts of the loop and to increase the amount of sample reading if those

operations are not taking place to balance the loop time and make practical use of this time. The first two

values are calculated using screen_on to ensure they are False if the screen is not being used.

The displayio library has a builtin optimisation. Only areas of the screen which have been changed are

sent to the TFT LCD screen. Internally these are processed as rectangular areas and marked as "dirty"

when they've been changed to indicate the need to send them to the screen on the next refresh.

Filters with and without ulab Library

The main loop also has an extra level of filtering to try to further reduce any brief, transient variations of

voltage - these could give a distracting, false indication. The simple code below shows how two previous

voltage values can be stored in simple variables. The _zm1 suffix refers to z which represents the unit

delay in digital filter implementations (https://adafru.it/La2).

# Store the previous two voltage values voltage_zm2 = voltage_zm1 voltage_zm1 = voltage

These are then used to make a "filtered" version of the voltage by a multiplication by weights (coefficients)

and summation.

# Make a filtered voltage from three values filt_voltage = (voltage * 0.4 + voltage_zm1 * 0.3 + voltage_zm2 * 0.3)

This tiny low-pass, causal filter (https://adafru.it/La3) was improvised rather than designed but appears to

work reasonably well to reduce the effect of transient spikes without introducing obvious delay.

CircuitPython 5.1.0 introduced the ulab (https://adafru.it/KaJ) library for boards with larger CPUs like the

-1

nRF52840 on the CLUE/CPB. This library is a cut-down version of numpy (https://adafru.it/HNf), providing

very fast vector operations and efficient, flexible storage for arrays. The ulab (https://adafru.it/La4)

approach for this can be seen on Low pass filtering: Measuring barometric Pressure (https://adafru.it/La5).

This type of filter is know as a Finite Impulse Response (FIR) (https://adafru.it/La6) filter. There is also a

convolve (https://adafru.it/La4) function in ulab which can be used to perform this type of filtering across

arrays.

The program does make some use of ulab . The unfiltered voltage values are continually stored in a fixed

size 201 element float -based ulab ndarray . This is used in the style of a circular

buffer (https://adafru.it/La7) storing the

most recent

201 values. These values are then used to calculate

the median (https://adafru.it/La8) voltage with the code shown below.

# Adjust the reference base_voltage to the median of historical values if voltage_hist_complete and update_median: voltage_hist_median = ulab.numerical.sort(voltage_hist)[len(voltage_hist) // 2] base_voltage = voltage_hist_median

The code is updating the baseline voltage used as the datum for calculating the voltage difference used

to indicate metal. This allows the code to deal with gradual shifts in the voltage level. An inevitable side-

effect of this approach is the detector will incorrectly adjust the baseline if held over a metal object

constantly for about ten seconds.

Magnetometer Baseline and Code Reviews

An informal code review by Jeff Epler (https://adafru.it/KPb) highlighted an inconsistency in the program

for setting the baseline value for the magnetometer. The code which initialises the values is shown below.

# Get a baseline value for magnetometer totals = [0.0] * 3 mag_samples_n = 10 if magnetometer is not None: for _ in range(mag_samples_n): mx, my, mz = magnetometer() totals[0] += mx totals[1] += my totals[2] += mz time.sleep(0.05)

base_mx = totals[0] / mag_samples_n base_my = totals[1] / mag_samples_n base_mz = totals[2] / mag_samples_n

The code used within the loop if the user pressed the right button to "Recalibrate" is a much simpler affair,

shown below.

# Excerpt from main loop inside if button_right(): if magnetometer is not None: base_mx, base_my, base_mz = mx, my, mz

The issues here could be summarised as:

There's no explanation in comments or documentation for this inconsistency.

There's no explanation for the 0.05 (50ms) pause in the for loop.

A developer working on this code in the future is left to guess the reasons for this and possibly

duplicate them without being able to justify the difference.

The actual reason for the difference is the calibration feature was added very late in the development

process and was not part of any initial design. The metal detector automatically adjusts the baseline for

the voltage which represents the inductance and presence of metal. It does not do this for the

magnetometer as this is a more stable value. In testing it turned out to be useful sometimes to set a new

baseline for the magnetometer so this was added as a feature initiated by pressing the right button.

The small delay in the first code sample was based on prior observations whilst developing the code for

CLUE Sensor Plotter in CircuitPython (https://adafru.it/La9). The magnetometer issues duplicate values if

read as fast as possible (~230Hz) in CircuitPython. This suggests it has a fixed rate for producing new

values and the library does not wait (block) for a new value to be produced. The adafruit_lis3mdl

library (https://adafru.it/Laa) shows a set of different rates but does not document the default (the code

shows it as 155Hz). The adafruit_clue library does not set an explicit rate which explains the duplication of

results.

There's no particular reason for the difference in the number of samples. This is worth checking

particularly on power-up to see if the sensor takes time to stabilise. The use case (https://adafru.it/Lab) for

user-initiated recalibration may specify it occurs within a certain amount of time - that would limit how

many samples could be taken. In practical use, the magnetometer value is fairly stable for tenths of

microteslas (uT).

This could be enhanced with:

A concise explanation in the comments and any documentation.

For both uses, call a

single

function which includes a parameter for the number of samples. This also

ensures any future modifications (software maintenance (https://adafru.it/EL9)) to the code are

applied to both.

ADC Analysis

The CLUE and Circuit Playground Bluefruit boards both use the nRF52840 System on a Chip

(SoC) (https://adafru.it/Fk-). This includes an analogue-to-digital converter (ADC) (https://adafru.it/Lac) using

the successive approximation (https://adafru.it/Lad) design. This is used in this project to measure the

voltage across a capacitor. CircuitPython configures this ADC in 12bit mode making each bit equivalent to

0.806mV.

This page explores the consistency of the ADC and the distribution of noise to determine if an average

value (arithmetic mean) over a certain number of samples is a valid approach to calculate an accurate

voltage.

Voltage across Capacitor in the Metal Detector

The graph below shows 1000 successive samples from the same function used in the program.

The samples are shown as dots which grow in size and are coloured relative to their distance from a fitted

(straight) line. This visualisation appears useful in confirming:

most values are near the line,

the distribution looks fairly even above and below the line(s),

a few values are

significantly

above or below the line but these also look reasonably evenly

distributed either side for this number of samples.

A second weighted line is also shown - this is a refinement created by weighting the points based on

their distance from the first line on a scale of 4 to 1. This reduces the large effect that

outliers (https://adafru.it/Lae) have using the least squares (https://adafru.it/Laf) approach to line fitting.

There's only a 0.2mV difference between this potentially more accurate line's arithmetic mean value and

the samples suggesting a basic, quick-to-calculate mean value gives a voltage with good accuracy. If the

sampling was reduced to, say 50 samples (over 2.4ms), then this looks more risky for an outlier having a

pronounced, adverse effect on the calculated mean voltage.

The curve fitting is an unnecessary leftover from when this graphing analysis code was used previously on

a capacitor

discharging

. In this case the capacitor is charging and discharging at a 400kHz rate. The

samples here have been gathered over ~47ms which covers over 18 thousand charge cycles. This means

the voltage will be largely constant with a miniscule amount of ripple.

In this case, it's possible these outliers are genuine but it seems unlikely that the voltage is really jumping

around because the:

1. difference is so great,

2. there's not an obvious "trail" of dots joining the spikes and

3. there's a capacitor involved.

The use of weighting for this analysis means they are not ignored, just downplayed based on the previous

justification. Statistics by Jim (https://adafru.it/Lag) has a useful guide on distinguishing

outliers (https://adafru.it/Lah) and deciding what to do with them (https://adafru.it/Lai). Discarding

inconvenient results is not a good justification!

This is a zoomed-in look at the lines. The scale exaggerates

the tiny gradient. The discrete ADC levels from 12bit sampling

can be see with the clearly defined rows of samples.

The P-P plot (https://adafru.it/Laj) and Q-Q

plot (https://adafru.it/Lak) are common plots for visually

comparing the data to another distribution, in this case the

normal distribution. A matching distribution will overlap the

straight line.

The histogram here is more of a bar chart as it's carefully

aligned with the quantized sample values.

Only the central

portion

of values is shown on this bar chart. This could show

any ADC peculiarities particularly with more graphs of

samples. There's nothing that jumps out as concerning here.

The choice of bucket size (width) for a histogram can have a large effect on the visual representation of

the data. If the data is quantised in some way then this effect can be more pronounced. Checking and

presenting varying bucket sizes is one way to avoid creating misleading charts. The animated graph

below shows different bucket sizes across the full range of sample values (voltages) with the data

presented with the mean subtracted making the central voltage 0mV.

A steady voltage reference source like a battery is a better test to look at the ADC. The results for two

1000 sample runs against an old alkaline AAA battery (https://adafru.it/Lal) are very similar to the graphs

above.

These tests were all conducted with the CLUE board powered by USB power from a desktop computer.

Some further testing would be useful, like:

1. Powering the CLUE from battery power with USB power removed to examine any adverse effects on

the ADC from noise on the power supply.

2. Comparing multiple CLUE boards and other boards based on the nRF52840.

3. Checking the distribution on the samples when measuring GND and 3.3V.

4. Checking different ADC acquisition times - this requires use of C++/Arduino.

5. Comparing software over-sampling with nRF52840 hardware over-sampling - this requires use of

C++/Arduino.

6. Looking at the sample data in the frequency domain to look for any periodic peculiarities. This will be

imperfect as the code in CircuitPython is not taking samples at a precise rate and the

jitter (https://adafru.it/Lam) will muddy everything except the very low frequencies.

Going Further

Ideas for Areas to Explore

Vary the coil size and windings to see how this affects the sensitivity.

Improve the magnetometer value as it currently only makes use of the z dimension.

Add a recent peak feature to the voltage bar graph and magnetometer circle.

If you are using the CPB without a screen:

Add some audio cues as time passes when the left button is depressed to give an indication of

the current menu option.

Conditionally disable the screen update code for a faster main loop or for better voltage

stability from increased sampling. The TFT Gizmo screen is not designed to be detectable but

the approach outlined in Adafruit Forums: Is it possible to detect presence of

Gizmo? (https://adafru.it/doW) is likely to work.

Related Projects

Adafruit Learn: Wireless Inductive Power Night Light (https://adafru.it/Lan)

Adafruit Learn: Cell Phone Charging Purse (https://adafru.it/Lao)

Adafruit Learn: Babel Fish (https://adafru.it/Lap) - RFID language learning toy with sound.

Adafruit Learn: Unlock Android Phone with Wearable NFC (https://adafru.it/dxA)

Adafruit Learn: Portal Apple Watch Charger (https://adafru.it/the)

Adafruit Blog: How to Build Your Own Metal Detector (https://adafru.it/fDK) - a project on

Instructables which uses a portion of a Dotstar strip (https://adafru.it/CIn) to indicate finds.

Adafruit CLUE Metal Detector User Manual

Specifications and Main Features

Frequently Asked Questions

User Manual