A novel method for detecting processes with multi-state modes

被引：15
作者：
Wang, Xiaoyang [1 ]
Wang, Xin [2 ]
Wang, Zhenlei [1 ]
Qian, Feng [1 ]
机构：
[1] E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China
[2] Shanghai Jiao Tong Univ, Ctr Elect & Elect Technol, Shanghai 200240, Peoples R China
来源：
CONTROL ENGINEERING PRACTICE | 2013年 / 21卷 / 12期
基金：
中国国家自然科学基金;
关键词：
FCM; CloneDE-HS; MVU; SVDD; Multiple-model detecting method; FAULT-DETECTION; DIAGNOSIS;
D O I：
10.1016/j.conengprac.2013.08.016
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Aiming at the muiltimode non-Gaussian process with within-mode nonlinearity, a fuzzy clustering multiple-model based inferential detecting method was proposed in this article. A clone-differential evolution-harmony search algorithm (CloneDE-HS) is used to search the best clustering centers of the process data. Then the operating data were classified as different modes. After that, maximum variance unfolding (MVU) were used to reduce the dimensions of each submodel variables. Furthermore the monitoring indices were constructed to detect the process fault. The model based support vector data description (SVDD) was built to detect the process. Finally, the proposed method was applied to detect an ethylene cracking furnace to demonstrate its efficiency. (C) 2013 Elsevier Ltd. All rights reserved.
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页码：1788 / 1794
页数：7
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