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Double moving window MPCA for Online adaptive batch monitoring
Alternative TitleDouble Moving Window MPCA for Online Adaptive Batch Monitoring
Zhao LJ1; Chai TY1; Wang G1
2005
Source PublicationCHINESE JOURNAL OF CHEMICAL ENGINEERING
ISSN1004-9541
Volume13Issue:5Pages:649-655
AbstractOnline monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database. In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA (multiway principal component analysis) model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA. The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride (PVC) process in the Jinxi Chemical Company of China since 1999.
Other AbstractOnline monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database. In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA (multiway principal component analysis) model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA. The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride (PVC) process in the Jinxi Chemical Company of China since 1999.
KeywordSYNCHRONIZATION moving window multiway principal component analysis batch monitoring
Indexed ByCSCD
Language英语
CSCD IDCSCD:2160830
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/150134
Collection中国科学院金属研究所
Affiliation1.东北大学
2.中国科学院金属研究所
Recommended Citation
GB/T 7714
Zhao LJ,Chai TY,Wang G. Double moving window MPCA for Online adaptive batch monitoring[J]. CHINESE JOURNAL OF CHEMICAL ENGINEERING,2005,13(5):649-655.
APA Zhao LJ,Chai TY,&Wang G.(2005).Double moving window MPCA for Online adaptive batch monitoring.CHINESE JOURNAL OF CHEMICAL ENGINEERING,13(5),649-655.
MLA Zhao LJ,et al."Double moving window MPCA for Online adaptive batch monitoring".CHINESE JOURNAL OF CHEMICAL ENGINEERING 13.5(2005):649-655.
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