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Multimode processes monitoring using global–local MIC-PCA-SVDD
Li S(李帅)1,2,3; Zhou XF(周晓锋)1,2,3; Shi HB(史海波)1,3; Wang ZW(王中伟)1,3
Department数字工厂研究室
Conference Name9th International Conference on Modelling, Identification and Control, ICMIC 2017
Conference DateJuly 10-12, 2017
Conference PlaceKunming, China
Source PublicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Publication PlaceSingapore
2017
Pages307-320
Indexed ByEI
EI Accession number20181805112286
Contribution Rank1
ISSN1876-1100
ISBN978-981-10-7211-6
KeywordMonitoring Multimode processes Multimode division Global–local MIC-PCA-SVDD
AbstractA multimode processes monitoring method using global–local MIC-PCA-SVDD is presented. Our method contains the procedures of mode division stage, offline modelling stage and online monitoring stage. At mode division stage, mode division using spectral clustering and multimode processes continuous characteristic is developed. It can divide multimode processes into multiple modes without priori multimode information. At offline modelling stage, considering multimode, global similarity and local non-similarity characteristics, global–local MIC-PCA-SVDD constructs multiple local models and a global model for monitoring. Our method considers dissimilarity between different modes and similarity in multimode processes. At online monitoring stage, different radiuses and distances between testing samples and the centre of the spheres using SVDD models are obtained for multimode processes monitoring. The advantages of SVDD in dealing with non-Gaussian and nonlinear data are used in our method. SVDD has no distribution assumption in which multimode processes data can be mapped to the high-dimensional feature space to construct multiple hyperspheres for global and local monitoring. The experiments of the penicillin fermentation processes are used to validate the feasibility and availability.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/22053
Collection数字工厂研究室
Corresponding AuthorLi S(李帅)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China;
3.Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, China
Recommended Citation
GB/T 7714
Li S(李帅),Zhou XF(周晓锋),Shi HB(史海波),等. Multimode processes monitoring using global–local MIC-PCA-SVDD[C]. Singapore:Springer Verlag,2017:307-320.
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