基于NGO-VMD-HHT的电缆局部放电信号特征量提取方法

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Abstract The phenomenon of partial discharge within a cable predominantly mirrors the insulation condition of cable-based equipment. Addressing a range of challenges encompassing the intricate extraction of partial discharge characteristic data and the inherent limitations pertaining to extraction precision during cable partial discharge detection, a feature extraction method based on northern goshawk optimization (NGO)-variational mode decomposition (VMD)-Hilbert-Huang transform (HHT) is proposed. Initially, the iterative application of the NGO is employed to determine the optimal configuration parameters essential for conducting VMD. Consequently, the optimal count of decomposition layers and the corresponding penalty factor are ascertained through this process. Then, the collected partial discharge signal is decomposed by VMD to obtain multiple modal components based on the optimal decomposition parameters. Finally, the Hilbert marginal spectrum theory is used to extract the characteristic components. The experimental results show that the feature extraction method of cable partial discharge based on NGO-VMD-HHT proposed in this paper can effectively decompose the partial discharge signal and accurately extract the corresponding feature quantity.

Key words： cable partial discharge variational mode decomposition (VMD) feature extraction northern goshawk optimization (NGO) Hilbert marginal spectrum

Received: 08 August 2023

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	Articles by authors
	LI Siyao
	DONG Zhang
	CHEN Yani
	LIU Hui
	YANG Hankun

Cite this article:

LI Siyao,DONG Zhang,CHEN Yani等. Feature extraction method of cable partial discharge signal based on NGO-VMD-HHT[J]. Electrical Engineering, 2023, 24(11): 35-41.

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http://dqjs.cesmedia.cn/EN/Y2023/V24/I11/35

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