运用自组织竞争网络进行气体定性分析的研究

Research of Gas Qualitative Analysis Using Self-organizing Competitive Network

优选了分析H2,CO气体的半导体气体传感器组成阵列,建立了实时数据采集系统,并与自组织竞争网络模式识别技术相结合,以进行气体定性分析的研究;同时为了消除气体浓度变化对传感器阵列输出的影响,提高自组织网络的识别效果,运用三种不同的数据归一化算法对传感器阵列的输出响应进行了预处理,并对各自对应的网络识别结果进行了分析与讨论。实验结果表明,采用相对算法可实现H2,CO气体的准确识别。

The semiconductor gas sensors sensitive to hydrogen and carbon monoxide are chosen to compose the gas sensor array, and an on-line data acquisition system is constructed, which is combined with the pattern recognition techniques of self organizing competitive network for the research of gas qualitative analysis. In order to eliminate the effect produced by the gas concentration, three kinds of normalization methods are developed to pre-process the sensors responses toward hydrogen and carbon monoxide. The research results show that the accurate identification of hydrogen and carbon monoxide in the finite range could be accomplished by relative method.