-
Notifications
You must be signed in to change notification settings - Fork 1
/
mq9.py
125 lines (106 loc) · 5.6 KB
/
mq9.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
# adapted from https://github.com/tutRPi/Raspberry-Pi-Gas-Sensor-MQ
import time
import math
from machine import ADC
class MQ:
# Hardware Related Macros
RL_VALUE = 10 # define the load resistance on the board, in kilo ohms
RO_CLEAN_AIR_FACTOR = 9.83 # RO_CLEAR_AIR_FACTOR=(Sensor resistance in clean air)/RO,
# which is derived from the chart in datasheet
# Software Related Macros
CALIBARAION_SAMPLE_TIMES = 50 # define how many samples you are going to take in the calibration phase
CALIBRATION_SAMPLE_INTERVAL = 500 # define the time interal(in milisecond) between each samples in the
# cablibration phase
READ_SAMPLE_INTERVAL = 50 # define how many samples you are going to take in normal operation
READ_SAMPLE_TIMES = 5 # define the time interal(in milisecond) between each samples in
# normal operation
# Application Related Macros
GAS_LPG = 0
GAS_CO = 1
GAS_SMOKE = 2
def __init__(self, ro=10):
self.ro = ro
self.adc = ADC(0)
self.LPGCurve = [2.3, 0.21, -0.47] # two points are taken from the curve.
# with these two points, a line is formed which is "approximately equivalent"
# to the original curve.
# data format:{ x, y, slope}; point1: (lg200, 0.21), point2: (lg10000, -0.59)
self.COCurve = [2.3, 0.72, -0.34] # two points are taken from the curve.
# with these two points, a line is formed which is "approximately equivalent"
# to the original curve.
# data format:[ x, y, slope]; point1: (lg200, 0.72), point2: (lg10000, 0.15)
self.SmokeCurve = [2.3, 0.53, -0.44] # two points are taken from the curve.
# with these two points, a line is formed which is "approximately equivalent"
# to the original curve.
# data format:[ x, y, slope]; point1: (lg200, 0.53), point2: (lg10000, -0.22)
print("Calibrating...")
self.ro = self.MQCalibration()
print("Calibration is done...\n")
print("Ro=%f kohm" % self.ro)
def MQPercentage(self):
val = {}
read = self.MQRead()
val["GAS_LPG"] = self.MQGetGasPercentage(read / self.ro, self.GAS_LPG)
val["CO"] = self.MQGetGasPercentage(read / self.ro, self.GAS_CO)
val["SMOKE"] = self.MQGetGasPercentage(read / self.ro, self.GAS_SMOKE)
return val
# MQResistanceCalculation
# Input: raw_adc - raw value read from adc, which represents the voltage
# Output: the calculated sensor resistance
# Remarks: The sensor and the load resistor forms a voltage divider. Given the voltage
# across the load resistor and its resistance, the resistance of the sensor
# could be derived.
def MQResistanceCalculation(self, raw_adc):
return float(self.RL_VALUE * (1023.0 - raw_adc) / float(raw_adc))
# MQCalibration
# Output: Ro of the sensor
# Remarks: This function assumes that the sensor is in clean air. It use
# MQResistanceCalculation to calculates the sensor resistance in clean air
# and then divides it with RO_CLEAN_AIR_FACTOR. RO_CLEAN_AIR_FACTOR is about
# 10, which differs slightly between different sensors.
def MQCalibration(self):
val = 0.0
for i in range(self.CALIBARAION_SAMPLE_TIMES): # take multiple samples
val += self.MQResistanceCalculation(self.adc.read())
time.sleep(self.CALIBRATION_SAMPLE_INTERVAL / 1000.0)
val = val / self.CALIBARAION_SAMPLE_TIMES # calculate the average value
val = val / self.RO_CLEAN_AIR_FACTOR # divided by RO_CLEAN_AIR_FACTOR yields the Ro
# according to the chart in the datasheet
return val
# MQRead
# Output: Rs of the sensor
# Remarks: This function use MQResistanceCalculation to caculate the sensor resistenc (Rs).
# The Rs changes as the sensor is in the different consentration of the target
# gas. The sample times and the time interval between samples could be configured
# by changing the definition of the macros.
def MQRead(self):
rs = 0.0
for i in range(self.READ_SAMPLE_TIMES):
rs += self.MQResistanceCalculation(self.adc.read())
time.sleep(self.READ_SAMPLE_INTERVAL / 1000.0)
rs = rs / self.READ_SAMPLE_TIMES
return rs
# MQGetGasPercentage
# Input: rs_ro_ratio - Rs divided by Ro
# gas_id - target gas type
# Output: ppm of the target gas
# Remarks: This function passes different curves to the MQGetPercentage function which
# calculates the ppm (parts per million) of the target gas.
def MQGetGasPercentage(self, rs_ro_ratio, gas_id):
if gas_id == self.GAS_LPG:
return self.MQGetPercentage(rs_ro_ratio, self.LPGCurve)
elif gas_id == self.GAS_CO:
return self.MQGetPercentage(rs_ro_ratio, self.COCurve)
elif gas_id == self.GAS_SMOKE:
return self.MQGetPercentage(rs_ro_ratio, self.SmokeCurve)
return 0
# MQGetPercentage
# Input: rs_ro_ratio - Rs divided by Ro
# pcurve - pointer to the curve of the target gas
# Output: ppm of the target gas
# Remarks: By using the slope and a point of the line. The x(logarithmic value of ppm)
# of the line could be derived if y(rs_ro_ratio) is provided. As it is a
# logarithmic coordinate, power of 10 is used to convert the result to non-logarithmic
# value.
def MQGetPercentage(self, rs_ro_ratio, pcurve):
return math.pow(10, (((math.log(rs_ro_ratio) - pcurve[1]) / pcurve[2]) + pcurve[0]))