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http://dx.doi.org/10.5302/J.ICROS.2012.18.6.540

A Study on a Fault Detection and Isolation Method of Nonlinear Systems using SVM and Neural Network  

Lee, In-Soo (Kyungpook National University)
Cho, Jung-Hwan (University of Massachusetts Lowell)
Seo, Hae-Moon (Korea Electronics Technology Institute)
Nam, Yoon-Seok (Dongguk University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.18, no.6, 2012 , pp. 540-545 More about this Journal
Abstract
In this paper, we propose a fault diagnosis method using artificial neural network and SVM (Support Vector Machine) to detect and isolate faults in the nonlinear systems. The proposed algorithm consists of two main parts: fault detection through threshold testing using a artificial neural network and fault isolation by SVM fault classifier. In the proposed method a fault is detected when the errors between the actual system output and the artificial neural network nominal system output cross a predetermined threshold. Once a fault in the nonlinear system is detected the SVM fault classifier isolates the fault. The computer simulation results demonstrate the effectiveness of the proposed SVM and artificial neural network based fault diagnosis method.
Keywords
fault detection; fault islolation; SVM; artificial neural network; nonlinear system;
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Times Cited By KSCI : 5  (Citation Analysis)
Times Cited By SCOPUS : 1
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