Application of electronic nose in gas mixture quantitative detection

Six semiconductor gas sensors which are sensitive to carbon monoxide (CO), methane (CH₄) and hydrogen (H₂) were chosen to compose the gas sensor array, and an on-line data acquisition system was constructed. Combining with the pattern recognition techniques of back propagation (BP) neuron network, the system was used to carry out the quantitative analysis of the partial gas concentration in a mixture. Pre-processing algorithms and the structures of the neural network was analyzed by experiments, and the results prove that the system can accomplish the quantitative analysis of the partial gas concentration of the mixture results using RRD pre-processing algorithm, then the training and testing of this three-layer BP neuron network with 9 neurons in hidden layer are performed.