Sinusoidal Noise Removal in PD Measurement Based on Synchrosqueezing Transform and Singular Spectrum Analysis

Shaorui Qin, Siyuan Zhou, Taiyun Zhu, Shenglong Zhu, Jianlin Li, Zheran Zheng, Shuo Qin, Cheng Pan and Ju Tang
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Shaorui Qin: State Grid AnHui Electric Power Research Institute, Hefei 230061, China
Siyuan Zhou: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Taiyun Zhu: State Grid AnHui Electric Power Research Institute, Hefei 230061, China
Shenglong Zhu: State Grid AnHui Electric Power Research Institute, Hefei 230061, China
Jianlin Li: State Grid AnHui Electric Power Research Institute, Hefei 230061, China
Zheran Zheng: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Shuo Qin: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Cheng Pan: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Ju Tang: School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Energies, 2021, vol. 14, issue 23, 1-22

Abstract: In electrical engineering, partial discharge (PD) measurement has been widely used for inspecting and judging insulation conditions of high voltage (HV) apparatus. However, on-site PD measurement easily becomes contaminated by noises. Particularly, sinusoidal noise makes it difficult to recognize real PD signal, thus leading to the misjudgment of insulation conditions. Therefore, sinusoidal noise removal is necessary. In this paper, instantaneous frequency (IF) is introduced, and the synchrosqueezing transform (SST) as well as singular spectrum analysis (SSA) is proposed for sinusoidal noise removal. A continuous analytic wavelet transform is firstly applied to the noisy PD signal and then the time frequency representation (TFR) is reassigned by SST. Narrow-band sinusoidal noise has fixed IF, while PD signal has much larger frequency range and time-varying IF. Due to the difference, the reassigned TFR enables the sinusoidal noise to be distinguished from PD signal. After synthesizing the signal with the recognized IF, SSA is further applied to signal refinement. At last, a numerical simulation is carried out to verify the effectiveness of the proposed method, and its robustness to white noise is also validated. After the implementation of the proposed method, wavelet thresholding can be further applied for white noise reduction.

Keywords: analytic wavelet; instantaneous frequency; partial discharge; sinusoidal noise removal; singular spectrum analysis; synchrosqueezed transform; time frequency representation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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