Volume 43 Issue 7
Jul.  2021
Turn off MathJax
Article Contents
ZENG Jun, WANG Dongjie, FAN Wei, LIU Binbin, ZHAO Hongshan. Research on Component Identification for Electrical Equipment Based on Infrared Thermography[J]. Infrared Technology , 2021, 43(7): 679-687.
Citation: ZENG Jun, WANG Dongjie, FAN Wei, LIU Binbin, ZHAO Hongshan. Research on Component Identification for Electrical Equipment Based on Infrared Thermography[J]. Infrared Technology , 2021, 43(7): 679-687.

Research on Component Identification for Electrical Equipment Based on Infrared Thermography

  • Received Date: 2020-12-25
  • Rev Recd Date: 2021-07-03
  • Publish Date: 2021-07-01
  • Common electrical equipment includes transformers, switchgears, and circuit breakers, which are composed of multiple components. In this study, the identification of these components was realized via infrared thermal imaging of such devices. Based on the characteristics of infrared thermal imaging with less information, a variety of algorithms have been used for fusion. First, based on the Lab model, a combination of improved K-means clustering and morphology was used to extract the high-temperature region in the infrared image, which guaranteed efficiency and reliability. Second, a combination of improved SURF and perceptual hash algorithms was used to determine the three-phase components in the extracted area. The role of SURF was to compare the visible image of the known electrical device with all the images in the extracted area to determine the area with the most matching feature points in the infrared image. Compared with other infrared regions, we found two regions with the highest matching degree in other regions via the perceptual hash algorithm to locate the three-phase devices in the infrared image. This study is applicable to infrared image recognition and positioning without a large number of image data sets and provides ideas for the extraction of fault information of electrical equipment based on infrared imaging.
  • loading
  • [1]
    韩军利. 红外图像目标识别技术研究[D]. 南京: 南京理工大学, 2004.

    HAN Junli. Research on Infrared Image Target Recognition Technology[J]. Nanjing: Nanjing University of Science and Technology, 2004.
    [2]
    戴文远. 基于红外热图像的故障诊断方法综述[J]. 红外, 2013, 34(2): 16-21. doi:  10.3969/j.issn.1672-8785.2013.02.03

    DAI Wenyuan. Review of fault diagnosis methods based on infrared thermal images[J]. Infrared, 2013, 34(2): 16-21. doi:  10.3969/j.issn.1672-8785.2013.02.03
    [3]
    冯振新, 周东国, 江翼, 等. 基于改进MSER算法的电力设备红外故障区域提取方法[J]. 电力系统保护与控制, 2019, 47(5): 123-128. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW201905015.htm

    FENG Zhenxin, ZHOU Dongguo, JIANG Yi, et al. Fault region extraction using improved MSER algorithm with application to the electrical system[J]. Power System Protection and Control, 2019, 47(5): 123-128. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW201905015.htm
    [4]
    LeeHyeon-Kyu, KimJH. An HMM-based threshold model approach for gesture recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(10): 961-973. doi:  10.1109/34.799904
    [5]
    林颖, 郭志红, 陈玉峰. 基于卷积递归网络的电流互感器红外故障图像诊断[J]. 电力系统保护与控制, 2015, 43(16): 87-94. doi:  10.7667/j.issn.1674-3415.2015.16.013

    LIN Yin, GUO Zhihong, CHEN Yufeng. Convolutional-recursive network based current transformer infrared fault imagediagnosis[J]. Power System Protection and Control, 2015, 43(16): 87-94. doi:  10.7667/j.issn.1674-3415.2015.16.013
    [6]
    陈伟, 何家欢, 裴喜平. 基于相空间重构和卷积神经网络的电能质量扰动分类[J]. 电力系统保护与控制, 2018, 46(14): 87-93. doi:  10.7667/PSPC171080

    CHEN Wei, HE Jiahuan, PEI Xipin. Classification for power quality disturbance based on phase-space reconstructionand convolution neural network[J]. Power System Protection and Control, 2018, 46(14): 87-93. doi:  10.7667/PSPC171080
    [7]
    林群武. 红外热成像技术在电力系统设备故障检测中的应用研究[D]. 淮南: 安徽理工大学, 2016.

    LIN Qunwu. Application of infrared thermal imaging technology in fault detectionof power system equipment [D]. Huainan: Anhui University of Science and Technology, 2016.
    [8]
    艾建勇, 金立军. 基于紫外图像的接触网棒瓷绝缘子污秽状态检测[J]. 电工技术学报, 2016, 31(10): 112-118. doi:  10.3969/j.issn.1000-6753.2016.10.013

    AI Jianyong, JIN Lijun. Rod porcelain insulator filth state detection of catenary based on ultraviolet image[J]. Transactions of China Electrotechnical Society, 2016, 31(10): 112-118. doi:  10.3969/j.issn.1000-6753.2016.10.013
    [9]
    周封, 任贵新. 基于颜色空间变量的输电线图像分类及特征提取[J]. 电力系统保护与控制, 2018, 46(5): 89-98.

    ZHOU Feng, REN Guixin. Image classification and feature extraction of transmission line based on color space variable[J]. Power System Protection and Control, 2018, 46(5): 89-98.
    [10]
    王志社, 杨风暴, 纪利娥, 等. 基于聚类分割和形态学的可见光与SAR图像配准[J]. 光学学报, 2014, 34(2): 184-190. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201402030.htm

    WANG Zhishe, YANG Fengbao, JI Li'e, et al. Optical and SAR image registration based on cluster segmentation and mathematical morphology[J]. Acta OpticaSinica, 2014, 34(2): 184-190. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201402030.htm
    [11]
    蒋景英, 张琪, 张昊, 等. 一种提高人耳特征点识别度的目标区域提取方法[J]. 纳米技术与精密工程, 2015, 13(4): 271-275.

    JIANG Jingying, ZHANG Qi, ZHANG Hao, et al. A target area detection method for improving ear feature point recognition degree[J]. Nanotechnology and Precision Engineering, 2015, 13(4): 271-275.
    [12]
    黄跃鑫, 钟舜聪, 伏喜斌, 等. 聚乙烯管道电熔接头的超声相控阵成像及缺陷特征[J]. 焊接学报, 2018, 39(2): 119-123, 134. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXB201802027.htm

    HUANG Yuexin, ZHONG Shuncong, FU Xifu, et al. Ultrasonic phased array imaging and defect characteristics of polyethylene pipe electrofusion joints[J]. Transactions of the China Welding Institution, 2018, 39(2): 119-123, 134. https://www.cnki.com.cn/Article/CJFDTOTAL-HJXB201802027.htm
    [13]
    黄新波, 刘新慧, 张烨, 等. 基于红蓝色差和改进K-means算法的航拍绝缘子分类识别方法[J]. 高电压技术, 2018, 44(5): 1528-1534. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ201805018.htm

    HUANG Xinbo, LIU Xinhui, ZHANG Ye, et al. Classification recognition method of insulator in aerial image based on the red-blue difference and developed K-means algorithm[J]. High Voltage Engineering, 2018, 44(5): 1528-1534. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYJ201805018.htm
    [14]
    李洪锋, 魏镜弢, 付亚伟, 等. 基于SIFT算法的物体运动方向快速识别方法[J]. 计算机工程与科学, 2019, 41(6): 1050-1056. doi:  10.3969/j.issn.1007-130X.2019.06.013

    LI Hongfeng, WEI Jingtao, FU Yawei, et al. A fast object motion direction recognition method based on SIFT algorithm[J]. Computer Engineering & Science, 2019, 41(6): 1050-1056. doi:  10.3969/j.issn.1007-130X.2019.06.013
    [15]
    李寒, 王库, 刘韶军. 基于灰度冗余和SURF算法的电气设备红外和可见光图像配准[J]. 电力系统保护与控制, 2011, 39(11): 111-115, 123. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW201111021.htm

    LI Han, WANG Ku, LIU Shaojun. Registration method between infrared and visible images of electrical equipment based on gray-scale redundancy and SURF[J]. Power System Protection and Control, 2011, 39(11): 111-115, 123. https://www.cnki.com.cn/Article/CJFDTOTAL-JDQW201111021.htm
    [16]
    杨瑞珍, 杜博伦, 何赟泽, 等. 晶体硅光伏电池电磁感应激励红外热辐射缺陷检测与成像技术[J]. 电工技术学报, 2018, 33(S2): 321-330. https://www.cnki.com.cn/Article/CJFDTOTAL-DGJS2018S2009.htm

    YANG Ruizhen, DU Bolun, HE Yunze, et al. Infrared radiation defect detection and imaging technique under active electromagnetic induction excitation for crystalline silicon photovoltaic cells[J]. Transactions of China Electrotechnical Society, 2018, 33(S2): 321-330. https://www.cnki.com.cn/Article/CJFDTOTAL-DGJS2018S2009.htm
    [17]
    崔行磊, 周学, 张勇, 等. 基于彩色摄像和光谱分析联合测温方法的电弧温度场分布测量[J]. 电工技术学报, 2017, 32(15): 128-135.

    CUI Xinglei, ZHOU Xue, ZHANG Yong, et al. Measurement of static Arc temperature distribution based on colorful photographing and spectroscopy analysis[J]. Transactions of China Electrotechnical Society, 2017, 32(15): 128-135.
    [18]
    李震, 洪添胜, 曾祥业, 等. 基于K-means聚类的柑橘红蜘蛛图像目标识别[J]. 农业工程学报, 2012, 28(23): 147-153, 299.

    LI Zhen, HONG Tiansheng, ZENG Xiangye, et al. Citrus red mite image target identification based on K-means clustering[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(23): 147-153.
    [19]
    李冠林, 马占鸿, 黄冲, 等. 基于K_means硬聚类算法的葡萄病害彩色图像分割方法[J]. 农业工程学报, 2010, 26(S2): 32-37. https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU2010S2008.htm

    LI Guanlin, MA Zhanhong, HUANG Chong, et al. Segmentation of color images of grape diseases using K_means clusteringalgorithm[J]. Transactions of the CSAE, 2010, 26(S2): 32-37. https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU2010S2008.htm
    [20]
    林滨. K-Means聚类的多种距离计算方法的文本实验比较[J]. 福建工程学院学报, 2016, 14(1): 80-85. https://www.cnki.com.cn/Article/CJFDTOTAL-JZGZ201601018.htm

    LIN Bin. Experimental comparison of K-Means text clustering by varied distance calculation methods[J]. Journal of Fujian University of Technology, 2016, 14(1): 80-85. https://www.cnki.com.cn/Article/CJFDTOTAL-JZGZ201601018.htm
    [21]
    胡兵, 杨明, 郭林栋, 等. 基于地面快速鲁棒特征的智能车全局定位方法[J]. 上海交通大学学报, 2019, 53(2): 203-208. https://www.cnki.com.cn/Article/CJFDTOTAL-SHJT201902011.htm

    HU Bing, YANG Ming, GUO Lindong, et al. Global localization for intelligent vehicles using ground SURF[J]. Journal of Shanghai Jiao Tong University, 2019, 53(2): 203-208. https://www.cnki.com.cn/Article/CJFDTOTAL-SHJT201902011.htm
    [22]
    纪利娥, 杨风暴, 王志社, 等. 可见光和红外反相图像的SURF特征双向匹配[J]. 光电工程, 2014, 41(5): 77-82. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC201405014.htm

    JI Li'e, YANG Fengbao, WANG Zhishe, et al. Bi-directional matching algorithm based on SURF featuresfor visible and negative image of infrared image[J]. Opto-Electronic Engineering, 2014, 41(5): 77-82. https://www.cnki.com.cn/Article/CJFDTOTAL-GDGC201405014.htm
    [23]
    牛夏牧, 焦玉华. 感知哈希综述[J]. 电子学报, 2008, 36(7): 1405-1411. doi:  10.3321/j.issn:0372-2112.2008.07.029

    NIU Xiamu, JIAO Yuhua. An overview of perceptual hashing[J]. Acta Electronica Sinica, 2008, 36(7): 1405-1411. doi:  10.3321/j.issn:0372-2112.2008.07.029
    [24]
    简献忠, 唐章源. 一种融合感知哈希的快速压缩跟踪算法[J]. 小型微型计算机系统, 2018, 39(11): 2503-2507. doi:  10.3969/j.issn.1000-1220.2018.11.028

    JIAN Xianzhong, TANG Zhangyuan. Fast compressive tracking algorithm based on perceptual Hashing[J]. Journal of Chinese Computer Systems, 2018, 39(11): 2503-2507. doi:  10.3969/j.issn.1000-1220.2018.11.028
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(11)  / Tables(2)

    Article Metrics

    Article views (419) PDF downloads(40) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return