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
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.
陈敬德, 李峰, 孙源文, 罗林根, 盛戈皞. 基于KNN和MSR的局部放电模式识别研究[J]. 电气技术, 2018, 19(1): 10-14.
Chen Jingde, Li Feng, Sun Yuanwen, Luo Lingen, Sheng Gehao. Research on pattern recognition of partial discharge based on KNN and MSR. Electrical Engineering, 2018, 19(1): 10-14.
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2018, Vol. 19 
