A study on a fault detection and isolation method of nonlinear systems using SVM and neural network

被引：0

作者：

Lee, In Soo ^{[1
]}

Cho, Jung Hwan ^{[2
]}

Seo, Hae Moon ^{[3
]}

Nam, Yoon Seok ^{[4
]}

机构：

[1] University of Massachusetts, Lowell, MA

来源：

Journal of Institute of Control, Robotics and Systems | 2012年 / 18卷 / 06期

关键词：

Artificial neural network; Fault detection; Fault islolation; Nonlinear system; SVM;

D O I：

10.5302/J.ICROS.2012.18.6.540

中图分类号：

学科分类号：

摘要：

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. © ICROS 2012.

引用

页码：540 / 545

页数：5

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