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In order to detect Volatile Organic Compounds (VOC) quickly and accurately, a portable electronic nose system was developed which including signal acquisition module, valve control module, embedded modules. Three sensors were used to measure methane, ethanol and formaldehyde gas. We used a three-way valve to control two kinds of gas, in order to avoid the system noise the zero reference was subtracted with the gas being tested. The system could quickly detect the three kinds VOC. The system can play a positive role in the rapid assessment of pollution in industrial parks.

The stochastic resonance (SR) theory provides a new idea for the detection of weak signal submerged in the strong noise. Combined with the optimization theory, this paper puts forward a stochastic resonance system based on genetic algorithm and applied it in a low concentrations gas detection. Firstly we preprocessed the input signal to satisfy the requirements of SR system, then developed the genetic algorithm to seek the maximum output signal-to-noise ratio (SNR), which was used to evaluate the performance of the system. In the end the relationship between the maximum SNR and concentration of gas was analyzed. The results of the experiments indicated the proposed method could improve the detection ability and enhance the detection limit of low gas concentrations.