A Novel Partial Discharge Ultra-High Frequency Signal De-Noising Method Based on a Single-Channel Blind Source Separation Algorithm

• Main Authors: Liangliang Wei, Yushun Liu, Dengfeng Cheng, Pengfei Li, Zhifeng Shi, Nan Huang, Hongtao Ai, Tianan Zhu
• Format: Article
• Language: English
• Published: MDPI AG 2018-02-01
• Series: Energies
• Subjects: partial discharge; blind source separation; de-noising performance; multi-channel signal; l1-norm minimization method
• Online Access: http://www.mdpi.com/1996-1073/11/3/509

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.