Abstract
To effectively de-noise the Gaussian white noise and periodic narrow-band interference in the background noise of partial discharge ultra-high frequency (PD UHF) signals in field tests, a novel de-noising method, based on a single-channel blind source separation algorithm, is proposed. Compared with traditional methods, the proposed method can effectively de-noise the noise interference, and the distortion of the de-noising PD signal is smaller. Firstly, the PD UHF signal is time-frequency analyzed by S-transform to obtain the number of source signals. Then, the single-channel detected PD signal is converted into multi-channel signals by singular value decomposition (SVD), and background noise is separated from multi-channel PD UHF signals by the joint approximate diagonalization of eigen-matrix method. At last, the source PD signal is estimated and recovered by the l1-norm minimization method. The proposed de-noising method was applied on the simulation test and field test detected signals, and the de-noising performance of the different methods was compared. The simulation and field test results demonstrate the effectiveness and correctness of the proposed method.
Highlights
Partial discharge (PD), which is caused by insulation defects, can be utilized to evaluate the insulation state of high voltage devices [1,2,3]
This paper proposed a novel partial discharge ultra-high frequency (PD ultra-high frequency (UHF)) de-noising method based on a single-channel blind source separation algorithm (BSS), which can effectively suppress the background noise interference of PD
This paper proposed a novel PD UHF signal de-noising method, based on a single-channel
Summary
Signal De-Noising Method Based on a Single-Channel Blind Source Separation Algorithm. Liangliang Wei 1,2 ID , Yushun Liu 3 ID , Dengfeng Cheng 3 , Pengfei Li 4, *, Zhifeng Shi 5 , Nan Huang 5 , Hongtao Ai 5 and Tianan Zhu 5. Received: 21 January 2018; Accepted: 24 February 2018; Published: 27 February 2018
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