A Cable Partial Discharge Localization Method Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise–Multiscale Permutation Entropy–Improved Wavelet Thresholding Denoising and Cross-Correlation Coefficient Filtering

Ting Zhu, Yuchen Lin, Hong Tian () and Youxiang Yan
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Ting Zhu: College of Electrical Engineering and Automation, Xiamen University of Technology, Xiamen 361000, China
Yuchen Lin: College of Electrical Engineering and Automation, Xiamen University of Technology, Xiamen 361000, China
Hong Tian: College of Electrical Engineering and Automation, Xiamen University of Technology, Xiamen 361000, China
Youxiang Yan: State Grid Fujian Electric Power Company, Xiamen Power Supply Company, Xiamen 361006, China

Energies, 2025, vol. 18, issue 20, 1-19

Abstract: Partial discharge (PD) source localization is an essential technology to identify the location of defects in power cables. This paper presents a complete cable PD localization system. To improve localization accuracy and reduce computational cost, the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise—Multiscale Permutation Entropy–Improved Wavelet Threshold (CEEMDAN-MPE-IWT) method is first employed to effectively suppress noise in PD signals. Subsequently, Cross-Correlation (CC) coefficients are calculated between the double-ended signals to eliminate low-quality signals with poor correlation. Furthermore, the retained signals are subjected to time-window cropping to minimize redundant data and enhance computational efficiency. Based on the processed signals, multiple time delay estimates are derived using the Generalized Cross-Correlation (GCC) algorithm, and the K-means clustering algorithm is subsequently applied to determine the final localization result. Finally, a cable PD experimental platform is established to validate the proposed method. Experimental results demonstrate that the proposed approach achieves a relative localization error of less than 3%, indicating high localization accuracy and strong potential for engineering applications.

Keywords: partial discharge localization; CEEMDAN-MPE-IWT denoising; cross-correlation coefficient filtering; K-means clustering (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: 2025
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