DENG Kun, WEN Qiliang, ZHANG Yuanyuan. Detection Method of Partial Discharge Defects in Cable Terminals Based on Ultrasonic Infrared Thermography[J]. Infrared Technology , 2022, 44(9): 972-978.
Citation: DENG Kun, WEN Qiliang, ZHANG Yuanyuan. Detection Method of Partial Discharge Defects in Cable Terminals Based on Ultrasonic Infrared Thermography[J]. Infrared Technology , 2022, 44(9): 972-978.

Detection Method of Partial Discharge Defects in Cable Terminals Based on Ultrasonic Infrared Thermography

More Information
  • Received Date: August 31, 2021
  • Revised Date: November 23, 2021
  • The partial discharge defect characteristics of cable terminals are short, and the defect range is entangled with the external environment, making it difficult to accurately locate. It must be detected along with the temperature characteristics and pattern recognition characteristics. In this paper, using the advantages of ultrasonic infrared thermal imaging, a partial discharge defect detection method for cable terminals based on ultrasonic infrared thermal images is proposed. This method uses image gradient grayscale to collect an ultrasonic infrared thermal image of the partial discharge defect characteristics of a cable terminal, suppress the complex background of the collected image via an intelligent pattern recognition processing method, and delete large-area ground objects and surfaces contained in the image. Using the K-means clustering algorithm, the characteristic range of the suspected partial discharge defects is delineated, and the partial discharge defect range template is constructed. After matching the reference range, information on the temperature characteristics of the suspected partial discharge defect range is obtained to diagnose whether there are partial discharge defects in the cable terminal. The experimental results show that this method can effectively obtain the partial discharge defects of cable terminals. The average accuracy of detecting different types of partial discharge defects in cable terminals was as high as 98%, and the average missed detection rate was 1%.
  • [1]
    孙永辉, 王馥珏, 邓鹏. 高压电缆局部放电带电检测技术的应用研究[J]. 南京理工大学学报: 自然科学版, 2019, 43(4): 505-510. https://www.cnki.com.cn/Article/CJFDTOTAL-NJLG201904018.htm

    SUN Yonghui, WANG Fujue, DENG Peng. Application of discharged detection technology for partial discharge of high voltage cable [J]. Journal of Nanjing University of Science and Technology, 2019, 43(4): 505-510. https://www.cnki.com.cn/Article/CJFDTOTAL-NJLG201904018.htm
    [2]
    米浩, 杨明, 于磊, 等. 基于超声红外热成像的缺陷检测与定位研究[J]. 振动·测试与诊断, 2020, 40(1): 101-106. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCS202001015.htm

    MI Hao, YANG Ming, YU Lei, et al. Research on defect detection and location based on ultrasonic infrared thermal imaging [J]. Journal of Vibration, Measurement & Diagnosis, 2020, 40(1): 101-106. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDCS202001015.htm
    [3]
    徐小冰, 袁婧, 廖雁群, 等. 基于Faster RCNN与Mean-Shift的电缆附件缺陷红外图像自动诊断方法[J]. 高电压技术, 2020, 46(9): 3070-3080. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202009010.htm

    XU Xiaobing, YUAN Jing, LIAO Yanqun, et al. Autonomous diagnosis method for defects of cable accessories based on faster RCNN and mean-shift algorithm by infrared images [J]. High Voltage Engineering, 2020, 46(9): 3070-3080. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202009010.htm
    [4]
    肖利龙, 吴海涛, 任重, 等. 基于多物理跟踪监测的电缆附件缺陷局部放电比值演化特征及诊断方法研究[J]. 电工电能新技术, 2020, 39(9): 28-35. https://www.cnki.com.cn/Article/CJFDTOTAL-DGDN202009005.htm

    XIAO Lilong, WU Haitao, REN Zhong, et al. Partial discharge evolution characteristics and diagnostic method of cable accessories based on multi-physical tracking [J]. Advanced Technology of Electrical Engineering and Energy, 2020, 39(9): 28-35. https://www.cnki.com.cn/Article/CJFDTOTAL-DGDN202009005.htm
    [5]
    周咏晨, 邹翔宇, 蓝耕, 等. 基于无人机红外热像的电缆隐患点智能检测[J]. 计算机系统应用, 2020, 29(8): 249-254. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYY202008036.htm

    ZHOU Yongchen, ZOU Xiangyu, LAN Geng, et al. Intelligently detecting hidden points of cables based on infrared thermal image of UAV [J]. Computer Systems & Applications, 2020, 29(8): 249-254. https://www.cnki.com.cn/Article/CJFDTOTAL-XTYY202008036.htm
    [6]
    杨志学, 汪正山, 叶雅婷, 等. 基于超声导波的长距离高压多芯电缆缺陷检测[J]. 无损检测, 2018, 40(12): 57-62. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC201812014.htm

    YANG Zhixue, WANG Zhengshan, YE Yating, et al. Defect detection for long distance high-voltage multi-core cable by using ultrasonic guided wave [J]. Nondestructive Testing, 2018, 40(12): 57-62. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJC201812014.htm
    [7]
    黄永禄, 周凯, 谢敏, 等. 基于改进CFSFDP算法的变频谐振下电缆局部放电脉冲分离方法[J]. 高电压技术, 2020, 46(12): 235-242. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202012028.htm

    HUANG Yonglu, ZHOU Kai, XIE Min, et al. Partial discharge pulse separation method for cables under variable frequency resonance based on improved CFSFDP [J]. High Voltage Engineering, 2020, 46(12): 235-242. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ202012028.htm
    [8]
    陈禾, 秦迎, 陈劲, 等. 基于红外热成像法和超声波法的钢管混凝土无损检测技术试验研究[J]. 建筑结构, 2020, 50(S1): 890-895. https://www.cnki.com.cn/Article/CJFDTOTAL-JCJG2020S1174.htm

    CHEN He, QIN Ying, CHEN Jin, et al. Experimental study on nondestructive testing technology of concrete filled steel tube based on infrared thermal imaging and ultrasonic method [J]. Architectural Structure, 2020, 50(S1): 890-895. https://www.cnki.com.cn/Article/CJFDTOTAL-JCJG2020S1174.htm
    [9]
    徐洋, 周电波, 丁登伟, 等. GIS盆式绝缘子表面缺陷的局部放电检测[J]. 高压电器, 2020, 56(5): 107-112. https://www.cnki.com.cn/Article/CJFDTOTAL-GYDQ202005017.htm

    XU Yang, ZHOU Dianbo, DING Dengwei, et al. Detection of partial discharge induced by surface defect of GIS basin insulators [J]. High Voltage Apparatus, 2020, 56(5): 107-112. https://www.cnki.com.cn/Article/CJFDTOTAL-GYDQ202005017.htm
    [10]
    郭蕾, 曹伟东, 张靖康, 等. 基于多尺度纹理特征的EPR电缆终端故障诊断方法[J]. 电力自动化设备, 2020, 40(11): 257-267. https://www.cnki.com.cn/Article/CJFDTOTAL-DLZS202011027.htm

    GUO Lei, CAO Weidong, ZHANG Jingkang, et al. Fault diagnosis method of EPR cable terminal based on multi-scale texture features [J]. Electric Power Automation Equipment, 2020, 40(11): 257-267. https://www.cnki.com.cn/Article/CJFDTOTAL-DLZS202011027.htm
    [11]
    汪可, 张书琦, 李金忠, 等. 基于灰度图像分解的局部放电特征提取与优化[J]. 电机与控制学报, 2018, 22(5): 29-38. https://www.cnki.com.cn/Article/CJFDTOTAL-DJKZ201805005.htm

    WANG Ke, ZHANG Shuqi, LI Jinzhong, et al. Partial discha RGE feature extraction and optimization based on gray image decomposition [J]. Electric Machines and Control, 2018, 22(5): 29-38. https://www.cnki.com.cn/Article/CJFDTOTAL-DJKZ201805005.htm
    [12]
    王笛, 沈涛. 复杂天空背景下的红外弱小目标检测算法研究[J]. 光学学报, 2020, 40(5): 103-110. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB202005011.htm

    WANG Di, SHEN Tao. Research on weak and small infrared target detection algorithm under complex sky background [J]. Acta Optica Sinica, 2020, 40(5): 103-110. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB202005011.htm
    [13]
    杨宁, 毕建刚, 弓艳朋, 等. 1100 kV GIS设备内部缺陷局部放电带电检测方法试验研究及比较分析[J]. 高压电器, 2019, 55(8): 37-47, 57. https://www.cnki.com.cn/Article/CJFDTOTAL-GYDQ201908006.htm

    YANG Ning, BI Jiangang, GONG Yanpeng, et al. Experimental research and comparative analysis on live test methods of partial discharge of internal defects in 1 100 kV GIS [J]. High Voltage Apparatus, 2019, 55(8): 37-47, 57. https://www.cnki.com.cn/Article/CJFDTOTAL-GYDQ201908006.htm
    [14]
    肖学文, 王亚淑, 刘康林. 基于红外热像技术的过程设备无损检测[J]. 化工机械, 2020, 47(6): 742-746. https://www.cnki.com.cn/Article/CJFDTOTAL-HGJX202006003.htm

    XIAO Xuewen, WANG Yashu, LIU Kanglin. Nondestructive Testing of Process Equipment Based on lnfrared Thermography [J]. Chemical Engineering & Machinery, 2020, 47(6): 742-746. https://www.cnki.com.cn/Article/CJFDTOTAL-HGJX202006003.htm
    [15]
    高治峰, 董丽虹, 王海斗, 等. 振动红外热成像技术用于不同类型缺陷检测的研究进展[J]. 材料导报, 2020, 34(9): 162-167. https://www.cnki.com.cn/Article/CJFDTOTAL-CLDB202009022.htm

    GAO Zhifeng, DONG Lihong, WANG Haidou, et al. Research progress and prospect of vibrothermography in different defect types [J]. Materials Review, 2020, 34(9): 162-167. https://www.cnki.com.cn/Article/CJFDTOTAL-CLDB202009022.htm
  • Related Articles

    [1]DENG Changzheng, LIU Mingze, FU Tian, GONG Mengqing, LUO Bingjie. Infrared Image Recognition of Substation Equipment Based on Improved YOLOv7-Tiny Algorithm[J]. Infrared Technology , 2025, 47(1): 44-51.
    [2]WANG Chongwen, PENG Tinghai, LUO Rui, LIU Jian, YANG Yuping, WANG Shijin, YAN Tingyu, GE Fan, LIU Yanfang, LIU Yunhong. Tropical Marine Environmental Adaptability of Germanium Coated Infrared Antireflection Film[J]. Infrared Technology , 2024, 46(8): 957-964.
    [3]ZHOU Huikui, ZHANG Li, HU Sujuan. Underwater Image Enhancement Based on Improved Histogram Matching and Adaptive Equalization[J]. Infrared Technology , 2024, 46(5): 532-538.
    [4]YANG Yuping, LIU Jian, ZHOU Xiaoyu, ZHAO Hongkun, LIU Yanfang, WANG Chongwen, ZHAO Yuanrong, GE Fan, XIAO Jianjun, LUO Rui, YANG Pinjie. Environmental Adaptability of Infrared Antireflection Films in Humid Hot Rain Forest[J]. Infrared Technology , 2021, 43(12): 1197-1201.
    [5]TANG Changming, ZHONG Jianfeng, ZHONG Shuncong, CHEN Man, FU Xibin, HUANG Xuebin. Ultrasound Infrared Thermography Defect Recognition Based on Improved Adaptive Genetic Algorithm with Two-Dimensional Maximum Entropy[J]. Infrared Technology , 2020, 42(8): 801-808.
    [6]WANG Chongwen, ZHAO Hongkun, LIU Jian, WANG Qiaofang, ZHU Guangyu, YANG Yuping, LUO Rui, ZHAO Yuanrong, LI Wei, LIU Yanfang, GE Fan. Dissecting the Adaptability of OLED Displays in Tropical Rainforest[J]. Infrared Technology , 2020, 42(6): 542-546.
    [7]JING Weiguo, SUN Mingzhao, LI Yongtao. Novel Experimental Method of Intense Light Adaptability of Night Vision Systems with Large Dynamic Range[J]. Infrared Technology , 2019, 41(7): 689-692.
    [8]LIU Hui, SHI Xiaolong. Improved GrabCut Segmentation Based on Salience and Superpixels[J]. Infrared Technology , 2018, 40(1): 55-61.
    [9]Improved Adaptive Segmentation Non-uniformity Correction Method for IRFPA[J]. Infrared Technology , 2017, 39(3): 209-213.
    [10]ZHANG Jin-cheng, LIAO Shou-yi, ZHANG Zuo-yu, SU De-lun, YAN Xun-liang. Real-time Improvement for Resistor Array Nonuniformity Correction[J]. Infrared Technology , 2015, 37(11): 921-925.
  • Cited by

    Periodical cited type(18)

    1. 田超华,赵欢,黄鸿基,孙伟可,王学峰. 基于深度学习的配电网开关柜电晕放电检测设计. 电子设计工程. 2025(01): 51-54+60 .
    2. 韩勇勇. 基于小波变换的PSO优化紫外双通道图像融合研究. 中国照明电器. 2025(02): 95-102 .
    3. 刘俊,王鲸,周炎生. 综合消磁工作线圈电缆接头击穿故障分析及应对策略. 广东造船. 2025(01): 59-62 .
    4. 朱杰,冯新颖,许网俊,范佳佳,杨赟. 基于YOLOV3神经网络的轨道车辆局部放电缺陷检测方法. 电工技术. 2025(03): 194-196 .
    5. 江澎,康正军,陈涛,冯一飞,吴琼. 融合人工智能与无线通信的热成像局放检测技术研究. 长江信息通信. 2024(01): 152-154 .
    6. 赵昊然,陆智勇,江明,刘立石. 小波包能量谱和神经网络的开关柜局部放电自动检测方法. 自动化与仪表. 2024(02): 92-96 .
    7. 汪可夫,胡志祥. 预制舱式变电站负荷支路漏电监测方法设计. 自动化仪表. 2024(07): 55-59+69 .
    8. 江熠,金坤鹏,钱锡颖,任一舟. 基于局部放电测试技术的避雷器状态诊断方法研究. 计算机测量与控制. 2024(07): 36-43 .
    9. 章铖. 基于红外热成像的变电站支柱绝缘子缺陷自动检测方法. 自动化技术与应用. 2024(08): 16-19+45 .
    10. 邵钦禹. 电力电缆的带电诊断与故障处理技术分析. 集成电路应用. 2024(09): 368-369 .
    11. 刘秀婷,李烨,高峰,马味敏. 高压电缆局部放电检测及识别系统研究. 电子测量技术. 2024(17): 97-107 .
    12. 胡梦捷. 基于非接触式测温技术的光伏直流侧拉弧线缆发热监测. 电线电缆. 2024(06): 31-34 .
    13. 韩勇勇,宋鹏,刘成涛. 基于ZYNQ 7020的双通道紫外放电检测系统设计. 国外电子测量技术. 2024(12): 115-120 .
    14. 苗堃,陈垒,李沛东,赵亚军,李健,郑城市,张胜利. 基于涡流技术的高压电缆铅封缺陷识别仿真研究. 环境技术. 2023(02): 139-145 .
    15. 龙丽名. 低压电线电缆检测手段及质量控制研究. 科技资讯. 2023(11): 42-45 .
    16. 何维晟,吴照国,徐扬,杜茂春,王谦,李勇,石钧仁. 高压电缆终端局部放电超声信号传输特性仿真分析. 高压电器. 2023(11): 48-55+64 .
    17. 刘杰,夏彦卫,贾伯岩,吴国强,殷庆栋. 基于高精度温度传感器的多股碳纤维导线潜伏性缺陷检测方法. 电子测量与仪器学报. 2023(11): 65-71 .
    18. 焦宇阳,段海南,张宏军,郑福建,朱进,刘新. 一种基于相关性分析和模糊规则的高压电缆状态评价方法. 电力大数据. 2022(10): 53-61 .

    Other cited types(11)

Catalog

    Article views (134) PDF downloads (25) Cited by(29)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return