基于Canny算法和图像处理的10 kV电缆中间接头典型施工缺陷识别

陈志; 方春华; 江全才; 于乔; 游海鑫

doi:10.13296/j.1001-1609.hva.2026.05.018

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基于Canny算法和图像处理的10 kV电缆中间接头典型施工缺陷识别

研究与分析 | 更新时间：2026-05-13

- 基于Canny算法和图像处理的10 kV电缆中间接头典型施工缺陷识别
- Identification of Typical Construction Defect in 10 kV Cable Intermediate Joints Based on Canny Algorithm and Image Processing
- 高压电器 2026年62卷第5期页码：157-165
- 作者机构：
  
  三峡大学电气与新能源学院，湖北宜昌 443002
  广东中山供电局，广东中山 528400
- 作者简介：
  
  陈志（2000—），男，硕士研究生，从事电气工程输电线路方向研究（E-mail：572451367@qq. com）。
  方春华（1980—），男，副教授，硕士生导师，从事电力系统在线监测技术、电力设备故障诊断、高电压绝缘与测试技术研究（通信作者）（E-mail：fang107531@163. com）。
- 基金信息：
  
  南方电网公司科技项目;Science and Technology Projects of China Southern Power Grid Company(032000KK52220033)
- DOI：10.13296/j.1001-1609.hva.2026.05.018
  中图分类号：
- 收稿：2025-08-10，
  
  修回：2025-11-02，
  
  纸质出版：2026-05-16
- 稿件说明：
移动端阅览
陈志, 方春华, 江全才, 等. 基于Canny算法和图像处理的10 kV电缆中间接头典型施工缺陷识别[J]. 高压电器, 2026,62(5):157-165.

CHEN Zhi, FANG Chunhua, JIANG Quancai, et al. Identification of Typical Construction Defect in 10 kV Cable Intermediate Joints Based on Canny Algorithm and Image Processing[J]. High Voltage Apparatus, 2026, 62(5): 157-165.
陈志, 方春华, 江全才, 等. 基于Canny算法和图像处理的10 kV电缆中间接头典型施工缺陷识别[J]. 高压电器, 2026,62(5):157-165. DOI： 10.13296/j.1001-1609.hva.2026.05.018.

CHEN Zhi, FANG Chunhua, JIANG Quancai, et al. Identification of Typical Construction Defect in 10 kV Cable Intermediate Joints Based on Canny Algorithm and Image Processing[J]. High Voltage Apparatus, 2026, 62(5): 157-165. DOI： 10.13296/j.1001-1609.hva.2026.05.018.

摘要

10 kV电缆中间接头施工缺陷易导致绝缘故障，为了快速准确的检测识别电缆中间接头施工缺陷，提出一种Canny算子和图像处理结合的边缘检测方法。Canny算子和图像处理结合的算法能最优定位边缘、不误检，得到准确的中间接头边缘信息。实验结果表明，Canny边缘算法能检测出缺陷图像中较为完整的污渍和划痕，对于主绝缘切割不齐、半导电剥离不齐和毛刺缺陷能准确的检测，缺陷算法准确率均达到90%以上。Canny边缘检测算法提高了缺陷检测的智能化程度，能有效管控施工质量。

Abstract

The construction defects of the 10 kV cable intermediate joint are easy to lead to insulation failure. For quickly and accurately detecting tand identifying the construction defects of cable intermediate joints

an edge detection method combining Canny operator and image processing is proposed. The algorithm combining Canny operator and image processing can locate the edge optimally without false detection

and obtain accurate edge information of intermediate joints. The experimental result shows that Canny edge algorithm can detect more complete stains and scratches in the defect image. The main insulation cutting

semi-conductive peeling and burr defects can be accurately detected

and the accuracy rate of the defect algorithm is more than 90%. The Canny edge detection algorithm improves the intelligence of defect detection and can effectively control the construction quality.

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references

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