Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 5
1409-1414

Time division fault diagnosis method based on KECA and FWA-SVM for batch process

Cai Zhenyu
Zhang Min
Bao Shanshan
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
DOI: 10.19734/j.issn.1001-3695.2017.12.0803

Abstract

Aiming at the high complexity, strong nonlinearity and strong time characteristics of intermittent process, this paper proposed a new method based on kernel entropy component analysis(KECA) to reduce the dimensionality of the KECA cha-racteristic variables, and used the fireworks algorithm(FWA) to optimize the support vector machine(SVM) parameters for the intermittent process of division fault diagnosis method. Firstly, it carried out multi-directional kernel principal component analysis(MKPCA) for the on-line fault monitoring and output the fault data. Second, it used K-means method to divide the batch process into several sub-periods. It used KECA to reduce characteristic variable dimensionality according to the contribution rate of entropy to determine the number of selected elements and extracted feature information in depth. Finally, it constructed FWA optimized SVM parameter fault diagnosis model in each sub-period, put the reduced dimension processed fault data into their own sub-period FWA-SVM diagnostic model for fault diagnosis. Through a variety of comparative experimental study based on penicillin simulation data, it verifies the feasibility and effectiveness of this method.

Foundation Support

中央高校基本科研业务费专项资金资助项目(2682016CX031)
国家自然科学基金资助项目(51675450)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.12.0803
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: Algorithm Research & Explore
Pages: 1409-1414
Serial Number: 1001-3695(2019)05-027-1409-06

Publish History

[2019-05-05] Printed Article

Cite This Article

蔡振宇, 张敏, 包珊珊. 基于KECA和FWA-SVM的间歇过程分时段故障诊断方法 [J]. 计算机应用研究, 2019, 36 (5): 1409-1414. (Cai Zhenyu, Zhang Min, Bao Shanshan. Time division fault diagnosis method based on KECA and FWA-SVM for batch process [J]. Application Research of Computers, 2019, 36 (5): 1409-1414. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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