层次式SVM子集含烃类混合气体光谱分析方法

含烃类混合气体具有组分多、组分浓度范围大的特点。为了解决海量混合气体光谱数据样本实际上是无法实现的难题，在大量调查的基础上，研究探索了实际工程中可能出现的混合气体分布模式，最后确定为15种混合气体分布子模式，共计5 500个光谱数据样本用于训练与检验。在此基础上，按照混合气体分布子模式识别→混合气体分析→结果输出的思路，提出了2层15子集的含烃类混合气体分析方法。多层次多子集软件集成框架以15种混合气体分布子模式为基本框架，由于应用了基于样本关联规则及混合气体分布模式中心集的SVM快速在线分类方法，可向原基本框架在线实时的加入新的混合气体分布子模式。实验结果显示，混合气体组分浓度分析的最大绝对误差为0.41%，最大平均绝对误差为0.04%。可用于其他混合气体的红外光谱分析，具有实际应用价值。

Method of Infrared Spectrum Analysis of Hydrocarbon Mixed Gas Based on Multilevel and SVM-Subset

The hydrocarbon mixed gas was characterized by multi-component and varied density. In order to deal with the difficulties that can not be actually solved with mass mixture gas spectrum data samples, 15 kinds of subset patterns were determined on the basis of investigations and studies, which needed 5 500 spectrum data samples for training and testing. On the basis of this, a method of hydrocarbon mixed gas infrared spectrum analysis based on 2-levels and 15 SVM-subsets was proposed in the light of the idea of working pattern recognition --> mixture gas analysis --> the final result output. In order to solve the problem of new subset working pattern, the SVM online categorization algorithm based on spectrum data relational rule was used. The experimental results show that the component concentration maximal deviation is 0.41% and the maximal average deviation is 0.04%. The method can be used in other mixture gas infrared spectrum analyses, and has the theoretic and application value.