Fault Diagnosis of Metro Vehicle Auxiliary Inverter Based on PSO-KPCM Algorithm

Zeng Tao Ma; Jun Wei Gao; Yong Qin; De Chen Yao; Bin Zhang

doi:10.4028/www.scientific.net/AMM.385-386.593

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 385-386Fault Diagnosis of Metro Vehicle Auxiliary...

Fault Diagnosis of Metro Vehicle Auxiliary Inverter Based on PSO-KPCM Algorithm

Abstract:

In this paper, the principle of kernel-based possibilistic clustering algorithm and particle swarm optimization algorithm are introduced and the application of the algorithms in fault diagnosis of auxiliary inverter is studied. Several common fault types are simulated by MATALB software. By initializing clustering center of samples based on PSO algorithm, calculating the final membership matrix and the final clustering center matrix based on the KPCM algorithm, the fault samples can be classified finally. The simulation results show that the PSO-KPCM algorithm can be used in the field of fault diagnosis. The PSO-KPCM algorithm even has better results and faster convergence rate than FCM algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 385-386)

Pages:

593-596

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.385-386.593

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Online since:

August 2013

Authors:

Zeng Tao Ma, Jun Wei Gao, Yong Qin, De Chen Yao, Bin Zhang

Keywords:

Fault Diagnosis, Kernel-Based Possibilistic Clustering, Particle Swarm Optimization (PSO)

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