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Research on fault diagnosis of industrial process based onimproved PCA method and data reconstruction(PDF)


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Research on fault diagnosis of industrial process based onimproved PCA method and data reconstruction
Du Hailian1Miao Shiyu2Du Wenxia1Lv Feng1
1.College of Career Technology,Hebei Normal University,Shijiazhuang 050024,China; 2.School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China
principal component analysis fault analysis fault reconstruction principal-component-related variable residual common variable residual production safety
Not only in order to determine the fault more accurately in the industrial system,but also in order to make the production system operation more stable,the improved principal component analysis method and data reconstruction method is used in the industrial process. The data of the normal and fault state of industrial system are collected,the SPE statistics of the traditional principal component analysis is divided into principal-component-related variable residual(PVR)and common variable residua(CVR),which are used to diagnose the system. In order to minimize the impact of the failure data on the system after detecting the failure,the data reconstruction method is further applied. The failure data are reconstituted into normal data,and the validity index is used to verify. When the fault happenes,the fault is repaired and excluded,and the failure impact on the production system is minimized. In order to verify the diagnosis method,the method is applied to the data of the Tennessee-Eastman system,the detection result of the fault is more precise,and the normal production system is ensured to work.


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Last Update: 2019-02-28