Volume fraction identification of NH3 and NO2 mixture gases based on sensor array and neural network algorithm
Aiming at the cross sensitivity of resistive gas sensors,volume fraction prediction technology of NH3 and NO2 mixture gases based on WO3 sensor array and neural network algorithm is developed.La-doped WO3 sensitive material synthesized by flame synthesis method and gas sensor is prepared,and constituent array with commercial MQ—137 resistive gas sensor.By extracting eigen value,neural network training,construct mapping model for sensor array output and gas volume fraction,and use this model to predict volume fraction of mixed gas of NH3,NO2 by the response result of sensor array.The experimental results illustrate that trained neural network can effectively predict the volume fraction of each component of mixed gas of NH3,NO2,the average prediction errors are 3.64%and 2.48%,respectively.The developed sensor array and neural network algorithm effectively avoid limitation of poor selectivity of resistive sensor,realize efficient identification and volume fraction measurement of mixed gas of NH3 and NO2.
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