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基于高压绝缘套管纹理特征的红外目标检测

赵洪山 张则言 孟航 张峻豪

赵洪山, 张则言, 孟航, 张峻豪. 基于高压绝缘套管纹理特征的红外目标检测[J]. 红外技术, 2021, 43(3): 258-265.
引用本文: 赵洪山, 张则言, 孟航, 张峻豪. 基于高压绝缘套管纹理特征的红外目标检测[J]. 红外技术, 2021, 43(3): 258-265.
ZHAO Hongshan, ZHANG Zeyan, MENG Hang, ZHANG Junhao. Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features[J]. INFRARED TECHNOLOGY, 2021, 43(3): 258-265.
Citation: ZHAO Hongshan, ZHANG Zeyan, MENG Hang, ZHANG Junhao. Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features[J]. INFRARED TECHNOLOGY, 2021, 43(3): 258-265.

基于高压绝缘套管纹理特征的红外目标检测

详细信息
    作者简介:

    赵洪山(1965-),男,汉族,河北沧州人,教授,博士生导师,研究方向为电力系统分析、运行与控制、智能配电网载波通信与自动化、电力设备故障预测与优化检修等。E-mail:zhaohshcn@126.com

  • 中图分类号: TP391.41

Infrared Target Detection of High Voltage Insulation Bushing Based on Textural Features

  • 摘要: 在基于传统图像分割法的红外图像目标检测中,当背景颜色和被检测物体颜色相近时,往往难以有效地识别红外图像中的被检测物。所以为了进一步提高绝缘套管在红外图像中的识别精度,文中提出一种基于绝缘套管伞裙纹理特征的目标检测方法。首先为增强图像纹理特性,将双边滤波代替传统高斯-拉普拉斯算子中的高斯卷积滤波,通过双边-拉普拉斯进行图像滤波和增强。之后针对高压绝缘套管外层伞裙的特殊纹理,建立反映伞裙周期性分布的描述子,并通过图像扫描法进行粗识别。最终基于DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法,建立其超参数求解方法,实现离群点剔除和特征聚类,完成高压绝缘套管的精细分割。通过实验对比其他绝缘套管红外图像的识别算法,文中算法可以有效地精细分割出绝缘套管主体,克服其他图像分割方法的不足。并在数据集上识别率达到85%以上。
  • 图  1  110 kV电容式电压互感器结构图

    Figure  1.  Configuration of 110 kV capacitance type voltage transformer

    图  2  典型滤波算子对比图

    Figure  2.  Comparison of typical filtering operators

    图  3  采样直线周期性特征

    Figure  3.  Sampling line periodic characteristics

    图  4  图像扫描法的粗识别

    Figure  4.  Preliminary recognition of image scanning method

    图  5  基于DBSCAN密度聚类的离群点剔除

    Figure  5.  Outlier removal based on DBSCAN density clustering

    图  6  目标检测识别方框

    Figure  6.  Object detection recognition box

    图  7  算法分割及识别效果对比图一

    Figure  7.  Three types of algorithm segmentation and recognition effect in the first comparison chart

    图  8  算法分割及识别效果对比图二

    Figure  8.  Three types of algorithm segmentation and recognition effect in the second comparison chart

    表  1  红外图像采集设备介绍

    Table  1.   Introduction of infrared image acquisition equipment

    Parameter Value Parameter Value
    Acquisition equipment FLIR T600 Measurement accuracy ±2℃
    Wavelength 7-13 μm Resolution 240×320
    Temperature range -40℃-130℃ Measuring distance 12-15 m
    下载: 导出CSV

    表  2  测试数据检测结果

    Table  2.   Results of test data

    The algorithm of paper Reference [18] Reference [19]
    IoU 0.766 0.649 0.703
    pre 0.872 0.673 0.746
    下载: 导出CSV
  • [1] 徐肖伟, 廖维, 王科, 等. 基于Havriliak-Negami介电模型的油浸式套管受潮状态评估[J]. 电测与仪表, 2018, 55(1): 53-59. doi:  10.3969/j.issn.1001-1390.2018.01.009

    XU Xiaowei, LIAO Wei, WANG Ke, et al. Moisture assessment of oil-impregnated bushing based on Havriliak-Negami dielectric relaxation model[J]. Electrical Measurement & Instrumentation, 2018, 55(1): 53-59. doi:  10.3969/j.issn.1001-1390.2018.01.009
    [2] 杨武, 王小华, 荣命哲, 等. 基于红外测温技术的高压电力设备温度在线监测传感器的研究[J]. 中国电机工程学报, 2002(9): 114-118. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC200209023.htm

    YANG Wu, WANG Xiaohua, RONG Mingzhe, et al. On-line temperature measurements with infrared technology on high voltage device[J]. Proceedings of the CSEE, 2002(9): 114-118. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC200209023.htm
    [3] 刘齐, 王茂军, 高强, 等. 基于红外成像技术的电气设备故障检测[J]. 电测与仪表, 2019, 56(10): 122-126, 152. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ201910020.htm

    LIU Qi, WANG Maojun, GAO Qiang, et al. Fault detection of electrical equipment based on infrared imaging technology[J]. Electrical Measurement & Instrumentation, 2019, 56(10): 122-126, 152. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ201910020.htm
    [4] 马承志, 王宇雷, 杨玺, 等. 用于变电站自主巡视机器人的图像传输系统研究[J]. 电力系统保护与控制, 2014, 42(18): 105-109. doi:  10.7667/j.issn.1674-3415.2014.18.018

    MA Chengzhi, WANG Yulei, YANG Xi, et al. Research on image transmission system for substation autonomous patrol robot[J]. Power System Protection and Control, 2014, 42(18): 105-109. doi:  10.7667/j.issn.1674-3415.2014.18.018
    [5] 黄山, 吴振升, 任志刚, 等. 电力智能巡检机器人研究综述[J]. 电测与仪表, 2020, 57(2): 26-38. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ202002005.htm

    HUANG Shan, WU Zhensheng, REN Zhigang, et al. Review of electric power intelligent inspection robot[J]. Electrical Measurement & Instrumentation, 2020, 57(2): 26-38. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ202002005.htm
    [6] 赵振兵, 金思新, 刘亚春. 基于NSCT的航拍绝缘子图像边缘提取方法[J]. 仪器仪表学报, 2012, 33(9): 2045-2052. doi:  10.3969/j.issn.0254-3087.2012.09.018

    ZHAO Zhenbing, JIN Sixin, LIU Yachun. Aerial insulator image edge extraction method based on NSCT[J]. Chinese Journal of Scientific Instrument, 2012, 33(9): 2045-2052. doi:  10.3969/j.issn.0254-3087.2012.09.018
    [7] 姚晓通, 刘力, 李致远. 基于Canny边缘特征点的接触网绝缘子识别方法[J]. 电瓷避雷器, 2020(1): 142-148. https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ202001024.htm

    YAO Xiaotong, LIU Li, LI Zhiyuan. Identification Method of Catenary Insulator Based on Canny Edge Feature Point[J]. Insulators and Surge Arresters, 2020(1): 142-148. https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ202001024.htm
    [8] 刘洋, 陆倚鹏, 高嵩, 等. 边缘检测在盘形悬式瓷绝缘子串红外图像上的应用[J]. 电瓷避雷器, 2020(1): 198-203. https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ202001033.htm

    LIU Yang, LU Yipeng, GAO Song, et al. Edge Detection on Infrared Image of High Voltage Porcelain Disc Type Suspension Insulator Strings[J]. Insulators and Surge Arresters, 2020(1): 198-203. https://www.cnki.com.cn/Article/CJFDTOTAL-DCPQ202001033.htm
    [9] 方挺, 董冲, 胡兴柳, 等. 航拍图像中绝缘子串的轮廓提取和故障检测[J]. 上海交通大学学报, 2013, 47(12): 1818-1822. https://www.cnki.com.cn/Article/CJFDTOTAL-SHJT201312002.htm

    FANG Ting, DONG Chong, HU Xingliu, et al. Contour extraction and fault detection of insulator strings in aerial images[J]. Journal of Shanghai Jiaotong University, 2013, 47(12): 1818-1822. https://www.cnki.com.cn/Article/CJFDTOTAL-SHJT201312002.htm
    [10] 杨政勃, 金立军, 张文豪, 等. 基于红外图像识别的输电线路故障诊断[J]. 现代电力, 2012, 29(2): 76-79. https://www.cnki.com.cn/Article/CJFDTOTAL-XDDL201202018.htm

    YANG Zhenbo, JIN Lijun, ZHANG Wenhao, et al. The Fault Diagnosis of Transmission Line Based on the Infrared Image Recognition[J]. Modern Electric Power, 2019, 29(2): 76-79. https://www.cnki.com.cn/Article/CJFDTOTAL-XDDL201202018.htm
    [11] SHI J Y, LIU J. Mentation based on modified region growing algorithm[J]. Optical Technique, 2017, 43(4): 381-384. http://en.cnki.com.cn/Article_en/CJFDTOTAL-GXJS201704019.htm
    [12] 崔巨勇, 曹云东, 王文杰. 基于分水岭与Krawtchouk不变矩相结合的改进方法在变电站巡检图像处理中的应用[J]. 中国电机工程学报, 2015, 35(6): 1329-1335. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201506006.htm

    CUI Juyong, CAO Yundong, WANG Wenjie. Application of an Improved Algorithm Based on Watershed Combined With Krawtchouk Invariant Moment in Inspection Image Processing of Substations[J]. Proceedings of the CSEE, 2015, 35(6): 1329-1335. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201506006.htm
    [13] 王媛彬, 尹阳. 基于红外弱目标提取的绝缘设备故障检测研究[J]. 红外技术, 2018, 40(2): 193-199. http://hwjs.nvir.cn/article/id/hwjs201802016

    WANG Yuanbin, YIN Yang. Research on the Insulation Equipment Fault Detection Based on Infrared Weak Target Extraction[J]. Infrared Technology, 2018, 40(2): 193-199. http://hwjs.nvir.cn/article/id/hwjs201802016
    [14] 刘元宁, 刘帅, 朱晓冬, 等. 基于高斯拉普拉斯算子与自适应优化伽柏滤波的虹膜识别[J]. 吉林大学学报: 工学版, 2018, 48(5): 1606-1613. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201805038.htm

    LIU Yuanning, LIU Shuai, ZHU Xiaodong, et al. LOG operator and adaptive optimization Gabor filtering for iris recognition[J]. Journal of Jilin University: Engineering and Technology Edition, 2018, 48(5): 1606-1613. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201805038.htm
    [15] 曾雅琼, 陈钱. 基于改进的双边滤波的单帧红外弱小目标背景抑制[J]. 红外技术, 2011, 33(9): 537-540. doi:  10.3969/j.issn.1001-8891.2011.09.011

    CENG Yaqiong, CHENG Qian. Dim and Small Target Background Suppression Based on Improved Bilateral Filtering for Single Infrared Image[J]. Infrared Technology, 2011, 33(9): 537-540. doi:  10.3969/j.issn.1001-8891.2011.09.011
    [16] CASSISI C, FERRO A, GIUGNO R, et al. Enhancing density-based clustering: Parameter reduction and outlier detection[J]. Information Systems, 2013, 38(3): 317-330. http://www.sciencedirect.com/science/article/pii/S0306437912001238
    [17] KUMAR K M, REDDY A R M. A fast DBSCAN clustering algorithm by accelerating neighbor searching using Groups method[J]. Pattern Recognition, 2016, 58: 39-48. http://www.sciencedirect.com/science/article/pii/S0031320316001035
    [18] 崔巨勇, 曹云东, 王文杰. 基于分水岭与Krawtchouk不变矩相结合的改进方法在变电站巡检图像处理中的应用[J]. 中国电机工程学报, 2018, 35(6): 1329-1335. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201506006.htm

    CUI Juyong, CAO Yundong, WANG Wenjie. Application of an Improved Algorithm Based on Watershed Combined With Krawtchouk Invariant Moment in Inspection Image Processing of Substations[J]. Proceedings of the CSEE, 2018, 35(6): 1329-1335. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDC201506006.htm
    [19] 吕欣欣. 红外图像分割算法研究及其在电气设备故障诊断中的应用[D]. 天津: 天津理工大学, 2019.

    LV Xinxin. Research on Infrared Image Segmentation Algorithm and its Application in the Fault Diagnosis of Electrical Equipment[D]. Tianjin: Tianjin University of Technology, 2019.
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  • 收稿日期:  2020-05-26
  • 修回日期:  2020-06-29
  • 刊出日期:  2021-04-02

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