Volume 7 Number 5 (May 2012)
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JCP 2012 Vol.7(5): 1204-1211 ISSN: 1796-203X
doi: 10.4304/jcp.7.5.1204-1211

Intelligent Fault Diagnosis of Steer-By-Wire Automobile

Fangyuan Wu, Feng Kong, Jiangyun Yao
Guangxi University of Technology, Liuzhou, China
Abstract—This paper presents an intelligent fault diagnostic approach for a steer-by-wire (SBW) system. A rough set model is utilized to reduce the redundant information. On the base of the reduction, the classifying rules can be extracted. A radical basis function (RBF) neural network optimized by particle swarm optimization (PSO) algorithm is designed to learn the fault rules that are extracted from the reduction of the redundant information. The proposed approach is simulated in MATLAB. Simulation results show that the proposed intelligent fault diagnostic algorithm provides a higher level of diagnostic accuracy than the approach without any optimization.

Index Terms—Fault diagnosis, steer-by-wire, rough set, radical basis function neural network, particle swarm optimization.

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Cite: Fangyuan Wu, Feng Kong, Jiangyun Yao, "Intelligent Fault Diagnosis of Steer-By-Wire Automobile," Journal of Computers vol. 7, no. 5, pp. 1204-1211, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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