I have an IR pyroelectic flame sensor which detects flames within the 8-10hz of flame flicker. I am new to the ADC world so any help is very appreciated.
Documentation: https://pyreos.com/wp-content/uploads/2020/11/Pyreos-Analog-TO-Flame-Sensor-One-Channel.pdf
I have the py0573 which has a bandpass filter for CO2 spectrum. According to the company's algorithm recommendation, I basically need to plot/detect FFT (Fast Fourier transform) bins from the 5-15hz frequency to determine a "flame" exists on the FOV of the sensor.
In order for me to read the signal from the half-rail, I installed a MCP3008 to my RPi model 4 and set the signal to CH0 of the ADC. I also included a .1uf decoupling capacitor.
Using the below code, I am able to get some readings from the sensor, but I am unsure if this sampling rate is setup correctly or not.
Questions:
- How do I setup the read from the ADC within the 8-10hz range?
- Is there a way to plot this with FFT? Do I need FFT or can I determine the total sum values from ADC to indicate a "flame"?
- Is the frequency setup basically the loop speed of Python or the spi.max_speed_hz option?
- Am I converting the raw ADC values correctly using numpy interp?
- If the sensor has a max 10hz frequency then I need to double that for my sample rate?
- Should I be using Adafruit's adafruit-circuitpython-mcp3xxx package instead?
With the below code, I am able to see the values change when I light a flicker match but its a bit inconsistent and only changes when the flame is flickering and not when its still.
import spidev
from numpy import interp
import time
import datetime
from datetime import timedelta
Start SPI connection
spi = spidev.SpiDev() # Created an object
spi.open(0,0)
Read MCP3008 data
def analogInput(channel, hz):
spi.max_speed_hz = hz
adc = spi.xfer2([1,(8+channel)<<4,0])
data = ((adc[1]&3) << 8) + adc[2]
return data
data_list=list()
init_time = datetime.datetime.now()
while True:
output1 = analogInput(0, 1000000)
output1 = interp(output1, [0, 1023], [0, 100])
data_list.append(output1)
if init_time < datetime.datetime.now() - timedelta(seconds=2):
print("min" + str(min(data_list)))
print("max" + str(max(data_list)))
print("avg" + str(sum(data_list)/len(data_list)))
data_list=list()
init_time = datetime.datetime.now()
time.sleep(.001)
