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Fault monitoring for batch process based on multi-stage ICA-SVDD(PDF)


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Fault monitoring for batch process based on multi-stage ICA-SVDD
Zheng Hao1Xiong Weili12
1.School of Internet of Things Engineering; 2.Key Laboratory of Advanced Process Control forLight Industry of Ministry of Education,Jiangnan University,Wuxi 214122,China
batch processes stage division independent component analysis support vector data description fault monitoring
In view of the characteristics of multi-stages and the non-Gaussian of the batch process,an improved stage division and fault monitoring method is proposed. Firstly,the stage is divided according to the similarity of each time slice and the k-means algorithm,and then the independent component analysis(ICA)method is used to extract the feature information of non-Gaussian of each stage respectively. Finally,the support vector data description(SVDD)algorithm is introduced to establish a statistical analysis model for the independent components and the remaining Gaussian residual spaces,and the whole process is monitored. The feasibility and effectiveness of the proposed method is verified by an actual fault monitoring application for the semiconductor etch process.


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Last Update: 2018-04-30