基于主成分分析法的工业废气污染源智能鉴别方法研究

Research on Intelligent Identification Method of Industrial Waste Gas Pollution Sources Based on Principal Component Analysis

针对现有方法难以提高工业废气污染源鉴别效果的问题,提出了一种基于主成分分析法的工业废气污染源智能鉴别方法研究。该方法先选取采样点位,采用循环式点位布置方法完成废气污染采样,然后采用不同胶合剂安装采样仪器,对采集样本进行预处理,利用空气喷射筛完成样本分化,最后采用主成分分析法得出废气污染的主成分序列,通过主成分回归得出智能鉴别结果。实验结果表明:所提方法可对不同类别工业废气污染进行鉴别,鉴别结果精确度较高。

Aiming at the problem that existing methods are difficult to improve the identification effect of industrial waste gas pollution sources,an intelligent identification method of industrial waste gas pollution sources based on principal component analysis is proposed.In this method,sampling points are selected first,sampling of exhaust gas pollution is completed by using the cyclic point layout method,sampling instruments are installed with different cement,samples are preprocessed,and sample differentiation is completed by using the air jet screen.Finally,principal component analysis is used to obtain the principal component sequence of exhaust gas pollution,and intelligent identification results are obtained by principal component regression.The experimental results show that the proposed method can identify different types of industrial waste gas pollution with high accuracy.