Car assembly line fault diagnosis based on robust wavelet SVC and PSO

Authors:
Qi Wu
Affiliations:
-
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

Citing 14
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Abstract

Aiming at some hybrid noises from complex fault diagnosis system, a robust loss function is designed to penalize hybrid noises, a wavelet kernel function is constructed on basis of wavelet base function, and then this paper proposes robust wavelet v-support vector classifier machine (RWv-SVC). To seek the optimal parameter of RWv-SVC, particle swarm optimization (PSO) is proposed. The results of application in fault diagnosis of car assembly line show the hybrid diagnosis model based on RWv-SVC and PSO is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves this method is better than v-SVC and Wv-SVC.