Component Spectrum Recognition for Mixed Gas Based on SVM
As for the problem that component gas characteristic spectrum lines overlaps seriously in the identification of Mixed Gas, Support Vector Machine is introduced for the identification, and an one-by-one identification methods for Mixed Gas classification based on the binary category identification model based on the support vector machine is proposed in this article. One-by-one category identification is carried out for each mixed gas when the characteristic spectrum lines are overlapped seriously and is transformed in high dimensional space into linear by SVM kernel function transformation. In the experiment for gas component identification of a natural gas, we compare the recognition results affected by different kernel functions, data preprocessing, feature extraction, numbers of training samples and other conditions. The results show that the method has the correct recognition rate of over 97％ for the natural gas whose concentration is over 1％, and it has a great promotional value both in theory and practical application.
Support vector machine Infrared spectrum Mixed gas Recognition model
Bai Peng Ji Juanzao Liu Peng Geng Daotian
Science Institute,Air Force Engineering University,Xian,China
国际会议
三亚
英文
557-560
2012-01-06（万方平台首次上网日期，不代表论文的发表时间）