Intelligent Sensing and Monitoring of Cable Joints’ State Based on Edge Computing

CAO Pei; XU Peng; GAO Kai; CHEN Fuchun; JIN Lijun

doi:10.13296/j.1001-1609.hva.2020.09.004

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Intelligent Sensing and Monitoring of Cable Joints’ State Based on Edge Computing

更新时间：2025-04-26

- Intelligent Sensing and Monitoring of Cable Joints’ State Based on Edge Computing
- High VoltageApparatus Vol. 56, Issue 9, Pages: 26-32(2020)
- 作者机构：
  
  1. 国网上海市电力公司电力科学研究院
  2. 同济大学
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2020.09.004
  CLC： TM75
- Published：2020
- 稿件说明：
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[1]曹培,徐鹏,高凯,谌福春,金立军.基于边缘计算的电缆接头运行状态智能传感与监测[J].高压电器,2020,56(09):26-32.

CAO Pei, XU Peng, GAO Kai, et al. Intelligent Sensing and Monitoring of Cable Joints’ State Based on Edge Computing[J]. High voltageapparatus, 2020, 56(9): 26-32.
[1]曹培,徐鹏,高凯,谌福春,金立军.基于边缘计算的电缆接头运行状态智能传感与监测[J].高压电器,2020,56(09):26-32. DOI： 10.13296/j.1001-1609.hva.2020.09.004.

CAO Pei, XU Peng, GAO Kai, et al. Intelligent Sensing and Monitoring of Cable Joints’ State Based on Edge Computing[J]. High voltageapparatus, 2020, 56(9): 26-32. DOI： 10.13296/j.1001-1609.hva.2020.09.004.

摘要

电缆接头是输配电中应用最为广泛的组件之一

现有外绝缘状态检测方法通常采集单一信号

易出现误检漏检

不利于故障的判断和预测。文中以变电站电缆接头为例

构建了有限元数学模型

进行了电场与温度场分布的仿真计算

为电缆接头外绝缘局部放电和温升检测提供理论依据。开发了基于边缘计算的检测单元

通过对电缆接头局部放电过程中释放的紫外和红外信号采集、数据传输、处理及特征辨识

为变电站电缆接头运行状态网络感知与判别提供支撑。采用自适应神经模糊系统（ANFIS）对两类信息进行融合分析

实现对电缆接头运行状态的智能传感与诊断。电缆接头局部放电实验显示

信息融合算法对电缆接头运行状态的判断准确率可达90%

研究成果有益于提升变电站的智能运维水平。

Abstract

Cable joint is one of the most widely used components in power transmission and distribution.The existing external insulation state detection methods usually collect a single signal

which is prone to false and missing detection

which is not conducive to fault judgment and prediction.In this paper

a finite element mathematical model of a cable joint is built to simulate the distribution of electric field and temperature

which provides theoretical basis for the detection of the external insulation discharge of the cable joint.A detection unit based on edge computing is designed

the ultraviolet and infrared signals released during partial discharge of cable joints are collected

data transmission

processing and feature identification are carried out to provide support for network perception and identification of substation cable joint operation state.The adaptive network-based fuzzy inference system（ANFIS） is used to fuse and analyze the two kinds of information to realize the intelligent sensing and diagnosis of the operation state of cable joints.The partial discharge experiment of a cable joint shows that the accuracy of information fusion algorithm to judge the operation state of cable joints can reach 90%.The research is beneficial to improve the intelligent operation and maintenance level of substations.

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