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《Advanced Technology of Electrical Engineering and Energy》 2002-03
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Study on pattern recognition of partial discharge in oil based on acoustic emission signals

ZHANG Lei, GAO Sheng-you, TAN Ke-xiong (Dept. of Electrical Engineering, Tsinghua University, Beijing 100084, China)  
In this paper, four kinds of models simulating partial discharge(PD) in oil are designed, and their acoustic emission signals of PD are detected. Two feature extraction methods are investigated, including the method extracting compressed data of the waveform and the method extracting the characteristic parameters in both time domain and frequency domain. Based on these methods, artificial network(ANN) is used to recognize the patterns of PD, and its effect is satisfactory. Additionally, some factors influencing the effect of recognition are also analyzed.
【Fund】: 国家自然科学基金资助项目 (5 99770 11)
【CateGory Index】: TM835.4
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