A Fault Diagnosis Approach of Steer-by-Wire System

Fang Yuan Wu; Feng Kong; Jiang Yun Yao

doi:10.4028/www.scientific.net/AMM.135-136.26

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 135-136A Fault Diagnosis Approach of Steer-by-Wire System

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.

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Periodical:

Applied Mechanics and Materials (Volumes 135-136)

Pages:

26-29

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.135-136.26

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Online since:

October 2011

Authors:

Fang Yuan Wu, Feng Kong, Jiang Yun Yao

Keywords:

Fault Diagnosis, Particle Swarm Optimization Algorithm (PSO), Radical Basis Function Neural Network, Rough Set (RS), Steering-by-Wire

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