电子鼻在气体混合物定量检测中的应用

Wu Pan, Ning Li, Pandeng Liu
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引用次数: 10

摘要

选取6个对一氧化碳(CO)、甲烷(CH4)和氢气(H2)敏感的半导体气体传感器组成气体传感器阵列,构建了在线数据采集系统。该系统结合BP神经网络模式识别技术,对混合气中部分气体浓度进行了定量分析。通过实验对预处理算法和神经网络的结构进行了分析,结果证明该系统采用RRD预处理算法可以完成混合气中部分气体浓度的定量分析结果,然后对隐含层有9个神经元的三层BP神经元网络进行了训练和测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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