Classification of partial discharge events in GILBS using discrete wavelet transform and probabilistic neural networks

Ming Shou Su, Jiann-Fuh Chen, Chien Yi Chen, Cheng-Chi Tai, Yu Hsun Lin

研究成果: Conference contribution

摘要

This paper proposes an approach to determining classification of partial discharge (PD) events in Gas Insulated Load Break Switches (GILBS). Discrete wavelet transform (DWT) is employed to suppress noises of measured signals by the high-frequency current transformer (HFCT). Three kinds of different defects are designed and placed inside three GILBS individually. For accurately determination of the different defect, feature extraction and statistics analysis of the measured signals are used in the proposed method. Finally, experimental results validate that the proposed approach can effectively discriminate the PD events in GILBS.

原文English
主出版物標題Proceedings of 2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012
頁面963-966
頁數4
DOIs
出版狀態Published - 2012 十二月 1
事件2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012 - Bali, Indonesia
持續時間: 2012 九月 232012 九月 27

出版系列

名字Proceedings of 2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012

Other

Other2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012
國家Indonesia
城市Bali
期間12-09-2312-09-27

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality

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  • 引用此

    Su, M. S., Chen, J-F., Chen, C. Y., Tai, C-C., & Lin, Y. H. (2012). Classification of partial discharge events in GILBS using discrete wavelet transform and probabilistic neural networks. 於 Proceedings of 2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012 (頁 963-966). [6416314] (Proceedings of 2012 IEEE International Conference on Condition Monitoring and Diagnosis, CMD 2012). https://doi.org/10.1109/CMD.2012.6416314