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中文摘要：
采用气体传感器阵列研究混合气体中各气体成分的体积分数，当气体成分的体积分数划分细致且组合种类多时，模式识别方法面临模式类别增多引起的神经网络结构复杂且训练时间长等问题．为了克服这一缺点，本文在使用一个四单元微热板式集成气体传感器阵列测试煤矿中的两种主要易燃易爆气体——一氧化碳和甲烷的基础上，将气体传感器阵列与盲信号分离技术相结合，讨论了混合气体分析的盲可辨识性，并使用盲信号分离中的一种主要方法——独立分量分析法（ICA）进行了分析和验证．
英文摘要：
Responses of a Micro-hotplate based integrated gas sensor array to CO and CH4 were measured with an automated gas sensor calibration system. Combining with the blind source separation（BSS） techniques, the blind separability in gas mixture analysis was discussed. The widely used BSS approach-Independent Component Analysis（ICA） was adopted to verify the proposed method by analyzing the gas mixtures of CO and CH4. The analysis results demonstrate that BSS was an effective way to extract the information of gas components in mixtures, from which the gas concentrations can be estimated. The average relative quantification errors were 9.37% and 8.11% for CO and CH4, respectively, in the specified concentration ranges.
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