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Added Linear ecuation on test algorithm
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@ -99,6 +99,13 @@ void loop()
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expectedValue[0] = 1000; expectedValue[1] = 3000; expectedValue[2] = 5000; expectedValue[3] = 7000;
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testSensor("MQ-309", 1000000, -4.01);
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// Testing linear equation for MQ-4
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mySensor.setRegressionMethod(0); //_PPM = pow(10, (log10(ratio)-b)/a)
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ratio[0] = 2.5; ratio[1] = 1.5; ratio[2] = 0.9; ratio[3] = 0.65;
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expectedValue[0] = 200; expectedValue[1] = 1000; expectedValue[2] = 5000; expectedValue[3] = 10000;
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testSensor("MQ-4", -0.318, 1.133);
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while(1);
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}
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@ -37,7 +37,7 @@ void setup() {
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Serial.begin(9600); //Init serial port
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//Set math model to calculate the PPM concentration and the value of constants
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MQ4.setRegressionMethod(0); //_PPM = a*ratio + b
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MQ4.setRegressionMethod(0); //_PPM = pow(10, (log10(ratio)-b)/a)
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@ -112,9 +112,9 @@ float MQUnifiedsensor::validateEcuation(float ratioInput)
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if(_regressionMethod == 1) _PPM= _a*pow(ratioInput, _b);
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else
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{
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// https://jayconsystems.com/blog/understanding-a-gas-sensor
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double ppm_log = (log10(_ratio)-_b)/_a; //Get ppm value in linear scale according to the the ratio value
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_PPM = pow(10, ppm_log); //Convert ppm value to log scale
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// https://jayconsystems.com/blog/understanding-a-gas-sensor
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double ppm_log = (log10(ratioInput)-_b)/_a; //Get ppm value in linear scale according to the the ratio value
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_PPM = pow(10, ppm_log); //Convert ppm value to log scale
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}
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//Serial.println("Regression Method: "); Serial.println(_regressionMethod);
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//Serial.println("Result: "); Serial.println(_PPM);
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