Journal of Shanghai Jiao Tong University

Journal of Shanghai Jiaotong University >

2023 , Vol. 57 >Issue 9: 1176 - 1185

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.299

Electronic Information and Electrical Engineering

Optical Feature Analysis and Diagnosis of Partial Discharge in C4F7N/CO2 Based on Multispectral Array

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  • 1. Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. Department of Light Sources and Illuminating Engineering, Fudan University, Shanghai 200433, China

Received date: 2022-07-25

  Revised date: 2022-09-25

  Accepted date: 2022-11-23

  Online published: 2023-03-10

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Abstract

Optical detection of partial discharge (PD) is an important way to reflect the insulation status of equipment. C4F7N/CO2 gas mixture is one of the most potential substitutes for SF6 at present, but there is a lack of research on its optical PD characteristics and diagnostic methods. In this paper, a PD multispectral array detection platform that can collect 7 characteristic bands is constructed, and 4 kinds of PD defects are produced. The similarities and differences of the PD multispectral characteristics in phase distribution, energy distribution, and feature stacking map under the conditions of 5 different ratios of C4F7N/CO2 gas mixture and pure SF6 gas are analyzed. Finally, a novel method of PD diagnosis based on multispectral features (MF) and k-nearest neighbors (KNN) is proposed. The experimental results show that the fault recognition accuracy in pure SF6 can reach 96.2%. The recognition rate of C4F7N/CO2 gas mixture is above 88%, and the highest accuracy rate is 91.1%. This method has a guiding significance for the PD diagnosis of environmentally friendly gas-insulated equipment, and provides a new route for traditional PD detection and diagnosis.

Key words： C4F7N/CO2; partial discharge (PD); multispectral array; optical detection; pattern recognition

Cite this article

LI Ze, QIAN Yong, ZANG Yiming, ZHOU Xiaoli, SHENG Gehao, JIANG Xiuchen . Optical Feature Analysis and Diagnosis of Partial Discharge in C4F7N/CO2 Based on Multispectral Array[J]. Journal of Shanghai Jiaotong University, 2023 , 57(9) : 1176 -1185 . DOI: 10.16183/j.cnki.jsjtu.2022.299

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