Paper Title:
A Fault Diagnosis Approach of Steer-by-Wire System
  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.

  Info
Periodical
Chapter
Chapter 1: Transportation & Service Science
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
26-29
DOI
10.4028/www.scientific.net/AMM.135-136.26
Citation
F. Y. Wu, F. Kong, J. Y. Yao, "A Fault Diagnosis Approach of Steer-by-Wire System", Applied Mechanics and Materials, Vols. 135-136, pp. 26-29, 2012
Online since
October 2011
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Price
$32.00
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