Power Transform Fault Diagnosis Based on the Adaptive Mutation Particle Swarm Optimization

Abstract:

In order to improve the accuracy of fault diagnosis of power transformer, in this paper, a method is proposed that optimize the weight of BP neural network by adaptive mutation particle swarm optimization (AMPSO). According to the characteristic of transformer fault, the optimized neural network is used to diagnose fault of the power transformer. Individual particles action is amended by this algorithm and local minima problems of the standard PSO and BP network are overcooked. The experimental results show that, the method can classify transformer faults, and effectively improve the fault recognition rate.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 3804-3808
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.3804
• Online since: September 2013
• Authors: Zhi Mei Duan, Jia Tang Cheng
• Keywords: Adaptive Mutation Particle Swarm Optimization, Fault Diagnosis, Power Transformer

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