Power Cable Fault Recognition Using the Improved PSO-SVM Algorithm

Abstract:

Power cables are increasingly popular in daily life and industrial production. The long-term use will make various cable faults. To reduce the losses caused by the faults, the cable faults should be recognized correctly and timely. In this paper, we developed an improved particle swarm optimization and support vector machine (IPSO-SVM) algorithm to recognize the power cable faults. The algorithm used the improved PSO to optimize the SVM kernel function parameter and the penalty parameter simultaneously. Two advantages were illustrated by the simulation experiments. The first one is the recognition accuracy which was increased from 81.8% to 90.9%; the second advantage is the SVM training time which decreased from 0.0247 second to 0.0202 second.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 830-833
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.830
• Online since: September 2013
• Authors: Mei Wang, Xiao Wei Li
• Keywords: Fault Recognition, Particle Swarm Optimization (PSO), Power Cable, Support Vector Machine (SVM)

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