Abstract:Monitoring of methane gas is one of the important factors affecting the coal mine safety. The online real-time monitoring of the methane gas is used for the mine safety protection. To improve the accuracy of model analysis, in the present paper, the author uses the technology of infrared spectroscopy to study the gas infrared quantitative analysis algorithm. By data mining technology application in multi-component infrared spectroscopy quantitative analysis algorithm, it was found that cluster analysis partial least squares algorithm is obviously superior to simply using partial least squares algorithm in terms of accuracy. In addition, to reduce the influence of the error on the accuracy of model individual calibration samples, the clustering analysis was used for the data preprocessing, and such denoising method was found to improve the analysis accuracy.
Key words:Infrared spectrum analysis;Methane gas;Partial least squares;Data mining
张爱菊 . 基于数据挖掘技术的瓦斯气体红外光谱定量分析方法的研究 [J]. 光谱学与光谱分析, 2013, 33(10): 2646-2650.
ZHANG Ai-ju . Study of Infrared Spectroscopy Quantitative Analysis Method for Methane Gas Based on Data Mining . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(10): 2646-2650.
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