Abstract：To solve the waveform distortions and uncertainties of traditional threshold methods and blind separation methods for periodic narrowband noise rejection of partial discharges (PD), this paper presents a noise rejection method based on improved FastICA algorithm. Firstly, in this paper, the number of periodic narrowband noise is determined by information entropy theory combined with mixed partial discharge DFT power spectrum, and the power spectrum “two steps” method is proposed to estimate the interference frequency accurately. Then the simplified Simpson-Newton iteration method and calibration signal are introduced to improve the FastICA algorithm, which can reduce iterations and modify the separated PD signal effectively. The simulation and experiment results show that: the proposed method can reject periodic narrowband noise and keep the original features of partial discharges effectively with low time complexity. Compared with frequency slice wavelet and FFT denoising method, the denoised PD signals using the method of this paper are better without edge effect.
周凯, 谢敏, 赵世, 林何珉, 张福忠. 基于改进FastICA的局部放电在线监测窄带干扰高保真性抑制方法[J]. 电工技术学报, 2018, 33(11): 2604-2612.
Zhou Kai, Xie Min, Zhao Shilin, He Min, Zhang Fuzhong. Periodic Narrowband Noise Rejection with High Fidelity of Partial Discharge on Line Monitoring Based on Improved FastICA Algorithm. Transactions of China Electrotechnical Society, 2018, 33(11): 2604-2612.
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2018, Vol. 33 
