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| Research on pattern recognition of partial discharge based on KNN and MSR |
| Chen Jingde1, Li Feng2, Sun Yuanwen2, Luo Lingen3, Sheng Gehao3 |
1. Qingpu District Power Supply Branch Company, Shanghai 201700;
2. Weihai Power Supply Company of Shandong Electric Power Company, Weihai, Shangdong 264200;
3. Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240 |
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Abstract In this paper, we propose a new method of partial discharge (PD) pattern recognition based on spectral distribution theory of random matrices. Firstly, the high dimensional random matrix is constructed by using the PD time domain signal received by the ultra high frequency sensor, the experiment use the Mean Spectral Radius (MSR) as the characteristic parameters of the PD pattern recognition based on the empirical spectral distribution theory of time series model under the random matrix theory. Then, we proposed the method of partial discharge pattern recognition based on K- nearest neighbor (KNN) algorithm. Theoretical research and experimental results show that this method has the characteristics of strong anti-interference ability and high recognition rate.
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Received: 06 July 2017
Published: 22 January 2018
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| Cite this article: |
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Chen Jingde,Li Feng,Sun Yuanwen等. Research on pattern recognition of partial discharge based on KNN and MSR[J]. Electrical Engineering, 2018, 19(1): 10-14.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2018/V19/I1/10
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2018, Vol. 19 
