可见光与红外图像融合的瓷绝缘子钢帽温度提取与零值检测方法研究
Research on Temperature Extraction of Porcelain Insulator Steel Cap and Zero Insulator Detection Based on Visible Light Image and Infrared Image
DOI: 10.12677/JISP.2023.122017, PDF,    国家自然科学基金支持
作者: 邹佳宸, 杨翔宇, 郑 重, 屠幼萍*：华北电力大学电气与电子工程学院，北京 ；胡 京, 王文彬, 李 帆：国网江西省电力有限公司，电力科学研究院，江西 南昌
关键词: 红外图像；零值绝缘子；钢帽分割；边缘检测；温度提取；Infrared Image； Zero-Value Insulator； Segmentation of Steel Cap； Edge Detection； Temperature Extraction
摘要: 瓷绝缘子钢帽温度分布的获取是输配电线路绝缘子零值缺陷巡检的关键一环，针对复杂背景下红外图像中绝缘子钢帽温度自动获取困难的现状，融合可见光与红外图像各自优点，基于Faster-RCNN深度学习网络算法检测可见光图像中的绝缘子串，检测率达98.3%；基于绝缘子强弱边缘特征改良Sobel算子检测绝缘子边缘；利用绝缘子钢帽的矩形形状特征、渐变间距特征实现所有钢帽的提取与修正；研究同场景下绝缘子在可见光与红外图像的坐标转换关系，实现红外图像中钢帽提取。在对110 kV和220 kV绝缘子进行零值缺陷检测时，本方法可以准确提取绝缘子钢帽温度并发现零值绝缘子，具有良好的有效性和实用性。
Abstract: Obtaining the temperature distribution of porcelain insulator steel cap is a key link in the patrol inspection of zero-value defects of transmission and distribution line insulators. It is difficult to obtain the temperature of insulator steel cap automatically in infrared image under complex background. Combining the respective advantages of visible and infrared images, insulator strings in visible light images are detected based on Faster-RCNN deep learning network algorithm, with a detection rate of 98.3%. The improved Sobel operator is used to detect the insulator edge based on the insulator strength edge feature. The rectangular shape feature and gradual spacing feature of insulator steel caps are used to extract and correct all steel caps. The coordinate conversion relationship between visible light and infrared image of insulator in the same scene is studied, and the steel cap extraction in infrared image is realized. When detecting zero-value defects of 110 kV and 220 kV insulators, this method can accurately extract the temperature of insulator steel cap and find zero-value insulators, which has good effectiveness and practicability.
文章引用：邹佳宸, 杨翔宇, 贺林轩, 胡京, 王文彬, 李帆, 郑重, 屠幼萍. 可见光与红外图像融合的瓷绝缘子钢帽温度提取与零值检测方法研究[J]. 图像与信号处理, 2023, 12(2): 169-179. https://doi.org/10.12677/JISP.2023.122017

参考文献

[1] 王万昆, 周学明, 胡丹晖, 等. 220 kV悬式瓷绝缘子零值原因研究[J]. 湖北电力, 2019, 43(5): 27-32.
[2] 陈瑶, 邹德华, 牛捷, 等. 500kV输电线路中低零值绝缘子对长串绝缘子电位和电场分布的影响[J]. 电瓷避雷器, 2015(3): 29-34.
[3] 范强, 罗浩, 曲锴, 等. 500 kV输电线路低零值绝缘子对绝缘子串电压分布的影响[J]. 绝缘材料, 2018, 51(12): 74-78.
[4] Yin, P.X., et al. (2018) The Influence of Low and Zero Resistance Insulators on the Voltage Distribution of Insulator Strings. 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), Wuhan, 31 May-2 June 2018, 2089-2094.
[Google Scholar] [CrossRef] 
[5] 郑维刚, 唐红, 朱义东, 等. 220 kV低零值绝缘子红外检测技术应用研究[J]. 东北电力技术, 2019, 40(11): 10-12.
[6] 廖威. 瓷质零值绝缘子在线检测中红外图像处理方法研究[D]: [硕士学位论文]. 长沙: 湖南大学, 2014.
[7] 黄军凯, 曾华荣, 杨佳鹏, 等. 红外热像技术在低零值绝缘子检测中的应用[J]. 电瓷避雷器, 2013(2): 40-44.
[8] 杨磊, 李爱华, 李宜平, 等. 输配电线路零值绝缘子红外检测技术研究[J]. 电工技术, 2022(13): 79-82.
[9] 谭孝元. 基于红外成像技术的零值绝缘子检测[D]: [硕士学位论文]. 成都: 西南交通大学, 2016.
[10] 李特, 刘黎, 巢亚锋, 等. 架空线路复合绝缘子现场红外测试研究现状评述[J]. 水电能源科学, 2020, 38(8): 184-187.
[11] 付强, 姚建刚, 李唐兵, 等. 基于红外图像的绝缘子串钢帽和盘面区域自动提取方法[J]. 红外技术, 2016, 38(11): 969-974+979.
[12] 刘正庭, 尹骏刚, 李凯迪, 汪宵飞, 王欣, 万勋, 姚建刚. 基于分水岭算法的绝缘子串红外图像分割方法[J]. 电瓷避雷器, 2020(2): 216-221+228.
[13] 苑利, 赵锐, 谭孝元, 苟先太. 基于红外成像技术的零值绝缘子检测[J]. 高压电器, 2018, 54(2): 97-102.
[14] Xiao, L.J., et al. (2017) A Fault Diagnosis Method of Insulator String Based on Infrared Image Feature Extraction and Probabilistic Neural Network. 2017 10th International Conference on Intelligent Computation Technology and Automation (ICICTA), Changsha, 9-10 October 2017, 80-85.
[Google Scholar] [CrossRef] 
[15] 刘云鹏, 张喆, 裴少通, 等. 基于深度学习的红外图像中劣化绝缘子片的分割方法[J]. 电测与仪表, 2022, 59(9): 63-68+118.
[16] 辛立杰. 基于深度学习的架空输电装备识别及其缺陷检测[D]: [硕士学位论文]. 北京: 华北电力大学.
[17] Girshick, R., Donahue, J., Darrell, T., et al. (2013) Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, 23-28 June 2014, 580-587.
[Google Scholar] [CrossRef] 
[18] Girshick, R. (2015) Fast R-CNN. 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, 7-13 December 2015, 1440-1448.
[Google Scholar] [CrossRef] 
[19] Ren, S., He, K., Girshick, R., et al. (2017) Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. IEEE Transactions on Pattern Analysis & Machine Intelligence, 39, 1137-1149.
[Google Scholar] [CrossRef] 
[20] Zhao, W., Xu, M., Cheng, X. and Zhao, Z. (2021) An Insulator in Transmission Lines Recognition and Fault Detection Model Based on Improved Faster RCNN. IEEE Transactions on Instrumentation and Measurement, 70, 1-8.
[Google Scholar] [CrossRef] 
[21] 王晶晶, 杨俊杰. 改进Canny算法在绝缘子串红外图像边缘检测中的应用[J]. 电瓷避雷器, 2022(3): 179-185.
[22] 马艳, 张治辉. 几种边缘检测算子的比较[J]. 工矿自动化, 2004(1): 54-56.
[23] 葛玉敏, 李宝树, 梁爽. 数学形态学在绝缘子图像边缘检测中的应用[J]. 高压电器, 2012, 48(1): 101-104, 109.
[24] 王柯, 陈驰, 彭向阳, 等. 基于无人机巡线可见光影像的电力设备中绝缘子的提取方法[P]. 中国, CN103488988A. 2014.
[25] 李文杰, 姚建刚, 毛李帆, 等. 基于中值滤波法及小波自适应扩散法的绝缘子红外热像去噪[J]. 电网技术, 2010, 34(8): 160-164.
[26] 杨雨, 蒋冰华, 张猛. 基于OTSUDE算法的零值绝缘子红外热像分割[J]. 电工技术, 2016(12): 1-3.
[27] DL/T 664-2016 带电设备红外诊断应用规范[S]. 北京: 中国电力企业联合会, 2016.