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Partial Discharge Pattern Recognition Using Radial Basis Function Neural Network

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1 Author(s)
Wen-Yeau Chang ; Dept. of Electr. Eng., St. John's Univ., Taipei, Taiwan

This paper proposed a novel radial basis function (RBF) neural network based recognition method to identify the insulation defects of high voltage electrical apparatus arising from partial discharge (PD). Basically, a defect of insulation, as resulting from PD, would have a corresponding particular pattern. Therefore, pattern recognition of PD is significant to discriminate insulation conditions of electrical apparatus. Pattern recognition of PD aims at recognizing the defects causing the PD, such as internal discharge, external discharge, or corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of insulators by using feature vectors of field-test PD patterns. The experimental data are found to be in close agreement. The test results show that the proposed approach is efficient and reliable.

Published in:

2010 Asia-Pacific Power and Energy Engineering Conference

Date of Conference:

28-31 March 2010