Partial Discharge Characteristics Research Based on RVM

Abstract:

In this paper, four original full typical UHF partial discharge signals are measured by using log-periodic antenna in 3-meter anechoic chamber environment. The relevance vector machine is applied for the study of partial discharge characteristics and the two relevance vector machine classifier are applied for the classification and identification of four partial discharge models. The experimental results are satisfactory. Compared with support vector machines, relevance vector machine can obtain more sparse classification model with probabilistic output value. It has a shorter test time and is more suitable for online testing. This method has a good prospect in partial discharge pattern recognition and online monitoring.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 1260-1263
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.1260
• Online since: July 2014
• Authors: Yue Heng Meng*, Hui Qi Li, Yang Hu
• Keywords: Feature Extraction, Partial Discharge (PD), Pattern Recognition, RVM

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