Key Technologies Research of Mixture Gas Infrared Spectrum Analysis Based on SVM
基于SVM的混合气体红外光谱分析关键技术研究

In order to solve the difficulties that mass mixture gas spectrum data samples cannot be actually obtain by mixture gas component characteristic absorption lines seriously overlap, component gas concentration distribution is optional, support vector machine was used in mixture gas infrared spectrum analysis. The spectrum data sample characteristic choice, the data pretreatment, and the SVM Calibration model parameter optimization and mixture gas spectral analysis structure based on level were summarized and proposed. The influence between analysis result and the above 4 key technologies was analyzed by the method of experimental. The experimental result shows that the mixture gas component concentration analysis based on the key technologies max absolute error is 2.93%; the mean absolute error is 0.73%.