Mechanical Defect Detection Method of High Voltage Circuit Breaker Based on Motion Trajectory Detection and Support Vector Machine

NIU Bo; WANG Xueli; WU Bing; YANG Dingge; GUO Yibo; LEI Sheng; ZHU Qianqian; ZHANG Guogang

doi:10.13296/j.1001-1609.hva.2024.08.004

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Mechanical Defect Detection Method of High Voltage Circuit Breaker Based on Motion Trajectory Detection and Support Vector Machine

Research & Analysis | 更新时间：2025-04-26

- Mechanical Defect Detection Method of High Voltage Circuit Breaker Based on Motion Trajectory Detection and Support Vector Machine
- High Voltage Apparatus Vol. 60, Issue 8, Pages: 29-36(2024)
- 作者机构：
  
  1.国网陕西省电力公司电力科学研究院，西安　 710100
  2.国网西咸新区供电公司，陕西　咸阳　 712000
  3.国网陕西省电力公司营销服务中心(计量中心)，西安　 710100
  4.西安交通大学电工材料电气绝缘全国重点实验室，西安　 710049
- 作者简介：
- 基金信息：
  
  Science and Technology Project of State Grid Shaanxi Electric Power Company(5226KY19004T)
- DOI：10.13296/j.1001-1609.hva.2024.08.004
  CLC：
- Received：13 January 2024，
  
  Revised：18 March 2024，
  
  Published：16 August 2024
- 稿件说明：
移动端阅览
NIU Bo, WANG Xueli, WU Bing, et al. Mechanical Defect Detection Method of High Voltage Circuit Breaker Based on Motion Trajectory Detection and Support Vector Machine[J]. High voltage apparatus, 2024, 60(8): 29-36.
DOI：

NIU Bo, WANG Xueli, WU Bing, et al. Mechanical Defect Detection Method of High Voltage Circuit Breaker Based on Motion Trajectory Detection and Support Vector Machine[J]. High voltage apparatus, 2024, 60(8): 29-36. DOI： 10.13296/j.1001-1609.hva.2024.08.004.

摘要

高压断路器是电网中的关键设备，机械缺陷是其主要故障类型，尽早发现潜在缺陷并及时进行维修意义重大。文中基于计算机视觉技术，提出一种采用角点跟踪法从动态图像中提取运动轨迹、支持向量机进行缺陷识别的高压断路器机械缺陷检测方法。首先，利用高速摄像机获取断路器操动机构的动作过程视频，通过角点跟踪算法获取拐臂角位移曲线；接着，通过主成分分析将高维特征向量降低为新空间中的低维特征向量；最后，利用支持向量机进行缺陷分类。实验测试结果表明，28组训练集、8组测试集的准确率分别为92.86%、87.5%，达到了良好的诊断效果。该方法作为一种非接触式测量方法，无需安装传感器，测量速度快，准确率高，对于现场检修具有重要意义。

Abstract

High-voltage circuit breaker is the key equipment in the power grid

mechanical defect is its main type of fault and it is important to diagnose the mechanical defect and perform maintenance in time. In this paper

a mechanical defect detection method based on computer vision

applying corner tracking method to extract motion trajectory and support vector machine to classify the defects

is proposed. Firstly

the high-speed camera is used to obtain the operation video of the operating mechanism of circuit breaker

and the angular displacement curve of the lever is obtained by corner tracking algorithm. Then

the high-dimensional feature vector is reduced to the low-dimensional feature vector by principal component analysis (PCA). Finally

the defect classification for reduced-dimensional feature vector is implemented by the support vector machine (SVM). The experimental test results show that the accuracy rate of 28 training sets and 8 test sets are 92.86%

87.5% respectively

and good detection results are achieved. The proposed method

as a kind of non-contact measurement method without installation of sensor

is fast in measurement speed and high in accuracy

and has important significance for the maintenance at site.

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