基于多光谱阵列的C4F7N/CO2混合气体局部放电光学特征分析与诊断

doi:10.16183/j.cnki.jsjtu.2022.299

上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (9): 1176-1185.doi: 10.16183/j.cnki.jsjtu.2022.299

所属专题：《上海交通大学学报》2023年“电子信息与电气工程”专题

基于多光谱阵列的C₄F₇N/CO₂混合气体局部放电光学特征分析与诊断

李泽¹, 钱勇¹(), 臧奕茗¹, 周小丽², 盛戈皞¹, 江秀臣¹

1.上海交通大学电气工程系, 上海 200240
2.复旦大学光源与照明工程系, 上海 200433

收稿日期:2022-07-25 修回日期:2022-09-25 接受日期:2022-11-23 出版日期:2023-09-28 发布日期:2023-09-27
通讯作者: 钱勇 E-mail:qian_yong@sjtu.edu.cn
作者简介:李泽(1997-),博士生,从事电力设备局部放电状态监测与智能化研究.
基金资助:
国家自然科学基金(62075045)

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

LI Ze¹, QIAN Yong¹(), ZANG Yiming¹, ZHOU Xiaoli², SHENG Gehao¹, JIANG Xiuchen¹

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:2022-07-25 Revised:2022-09-25 Accepted:2022-11-23 Online:2023-09-28 Published:2023-09-27
Contact: QIAN Yong E-mail:qian_yong@sjtu.edu.cn

摘要/Abstract

摘要：

局部放电(PD)的光学检测是反映设备绝缘状态的重要方法.C₄F₇N/CO₂混合气体是目前最具有潜力的SF₆替代气体,但是缺乏针对该混合气体光学PD特性和诊断方法的研究.构建了一个可采集7个特征波段的PD多光谱阵列检测平台,制作了4种PD缺陷,分析了5种不同比例的C₄F₇N/CO₂混合气体和纯SF₆气体条件下多光谱PD特征在相位分布、能量分布和特征堆叠图的异同,提出了一种基于多光谱特征(MF)和最近邻算法(KNN)的PD诊断新方法.实验结果表明,纯SF₆故障识别准确率可达96.2%;C₄F₇N/CO₂混合气体的识别率在88%以上,最高准确率为91.1%.该方法对环保型气体绝缘设备的PD诊断具有指导意义,也为传统的PD检测和诊断提供了新思路.

关键词: C₄F₇N/CO₂, 局部放电, 多光谱阵列, 光学检测, 模式识别

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

中图分类号:

TM855

李泽, 钱勇, 臧奕茗, 周小丽, 盛戈皞, 江秀臣. 基于多光谱阵列的C₄F₇N/CO₂混合气体局部放电光学特征分析与诊断[J]. 上海交通大学学报, 2023, 57(9): 1176-1185.

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 Jiao Tong University, 2023, 57(9): 1176-1185.

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滤光片	波长/nm	透光率/%
LF0	全波段	全透
LF1	630~1100	>90
LF2	582~593	>85
LF3	510~545	>83
LF4	260~380	>90
LF5	460~500	>90
LF6	400~445	>85

算法	分类准确率/%
算法	4%C₄F₇N	6%C₄F₇N	8%C₄F₇N	10%C₄F₇N	12%C₄F₇N	SF₆
MF-SVM	81.1	83.7	88.5	86.6	87.5	94.4
MF-DT	85.1	83.1	87.7	86.8	88.0	94.8
MF-KNN	90.6	88.7	91.1	89.1	90.0	96.2

基于多光谱阵列的C₄F₇N/CO₂混合气体局部放电光学特征分析与诊断

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

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