Dynamic independent component analysis approach for fault detection and diagnosis

被引：88

作者：

Stefatos, George ^{[2
]}

Ben Hamza, A. ^{[1
]}

机构：

[1] Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ, Canada

[2] Pratt & Whitney, Longueuil, PQ, Canada

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期

关键词：

Fault detection; Fault analysis and diagnostics; Dynamic independent component analysis; Multivariate process control; PCA;

D O I：

10.1016/j.eswa.2010.06.101

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we introduce a novel fault detection and diagnosis method using a dynamic independent component analysis-based approach. We also present an innovative mechanism for detecting and diagnosing the faults. The proposed approach is able to accurately detect and isolate the root causes for each individual fault. The Tennessee Eastman challenge process is used to demonstrate the much improved performance of our proposed technique in comparison with other currently existing statistical monitoring and fault detection methods. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：8606 / 8617

页数：12

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