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Fault detection based on global-local PCA-SVDD for multimode processes
Li S(李帅); Zhou XF(周晓锋); Shi HB(史海波); Wang ZW(王中伟)
作者部门数字工厂研究室
会议名称9th International Conference on Modelling, Identification and Control, ICMIC 2017
会议日期July 10-12, 2017
会议地点Kunming, China
会议录名称Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017
出版者IEEE
出版地New York
2017
页码863-868
收录类别EI
EI收录号20183105620632
产权排序1
ISBN号978-1-5090-6573-8
关键词fault detection monitoring multimode industrial processes mode division global-local PCA-SVDD
摘要Fault detection is of importance for industrial processes with complex characteristics including multimode. In this paper, a fault detection method based on global-local PCA-SVDD is proposed for multimode industrial processes. Firstly, mode division based on spectral clustering is presented, which divides multimode processes into multiple modes without priori multimode information. Then, considering the multimode characteristic, global similarity and local non-similarity, the global-local PCA-SVDD models are built, which decomposes fault detection into a global model and multiple local models. Finally, different statistics and confidence limits are used for different models. The experiment results of the penicillin fermentation processes illustrate the feasibility and effectiveness of the proposed method for multimode industrial processes.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/22361
专题数字工厂研究室
通讯作者Li S(李帅)
作者单位Shenyang Institute of Automation, Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang, China
推荐引用方式
GB/T 7714
Li S,Zhou XF,Shi HB,et al. Fault detection based on global-local PCA-SVDD for multimode processes[C]. New York:IEEE,2017:863-868.
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