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《Proceedings of the Csee》 2004-05
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LIU Yun-peng, LU Fang-cheng, LI Cheng-rong (School of Electrical Engineering, North China Electric Power University, Baoding 071003, China)  
Partial discharge (PD) pattern recognition is an effective method to evaluate insulation condition of high voltage apparatuses and distinguish external pulse interferences. As a morphological image tool, granulometry is useful for estimating object size and granularity in grayscale image, or characterizing textures based on their pattern spectrum. This paper brings forward a method to extract PD pattern spectrums based on mathematical morphological multi-scale opening operation. The pattern spectrum is used as feature of PD grayscale image. Six kinds of typical discharge models are designed and their pattern spectrums are calculated, then a double hidden-layer neural network is applied for PD pattern recognition. The analytical results show that the proposed method is effective for PD pattern recognition.
【CateGory Index】: TM831
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