In order to solving the problem that the mass samples of mixed gas spectra data samples being unable to obtain, characteristic absorption spectrum line of the component gas for mixed gas being overlap, and the problem of randomness of component concentration distribution for mixed gas and so on, support vector machine is introduced for the infrared spectra analysis for the mixed gas. Key technologies as feature selection of spectra data samples, data preprocessing, SVM calibration model parameters optimization and level structure for spectrum analysis of a mixed gas is proposed in the paper. The influence of above-mentioned four key technologies to the analysis results is discussed by using experimental means. The experimental result shows that with adoption of the key technologies, the maximum absolute error of component concentration analysis for the mixed gas is 2.93%, and the maximum average absolute error is of 0.73%. The method can also be used for infrared spectra analysis for other mixed gas, and it has practical application value.