固体绝缘开关柜在线检测技术

doi:10.11930/j.issn.1004-9649.2016.09.035.06

摘要/Abstract

摘要： 固体绝缘开关柜挂网运行过程中,其柜内的一次高压部件热功率很大,易导致局部过热,从而造成开关柜的短路故障。为了确保配电网的稳定、安全与可靠运行,提出了一种固体绝缘开关柜在线检测新技术。它首先获取开关柜关键部位的原始红外热图像数据,借助配电网电力多模通信接入切换装置将检测信息以230 Mesh（无线Mesh网络）、光纤等多种通信方式,传输到配电网自动化主站,预处理、噪声滤除、图像增强、图像边缘检测,分析红外热图像数据处理结果后,进行固体绝缘开关柜的过热故障诊断。这种新技术的实用性已被具体的实验和工程验证,简化了配电网固体绝缘开关柜的检修工作。

关键词: 固体绝缘, 开关柜, 故障诊断, 红外热成像, 多模通信, 电气接头

Abstract: Large thermal power in high voltage insulation unit often leads to serious local heat and short circuit fault. In order to ensure distribution power grid stability, security and reliability, a novel on-line detection technology is proposed for solid insulation ring main unit(RMU). Firstly, the original infrared thermal image is obtained and transmitted to distribution automation system master station by using different communication modes including 230 Mesh and fiber. The image is analyzed after preprocessing, noise filtering, image enhancement, and edge detection to detect fault in solid insulated RMU. This novel technology can diagnose electrical joints accurately comparing to traditional contact measurement method.

Key words: solid insulation, RMU, fault diagnosis, infrared thermal imaging, multi-mode communication, electrical joints

中图分类号:

TM72

叶海蓉, 葛乐矣, 钟桂英. 固体绝缘开关柜在线检测技术[J]. 中国电力, 2016, 49(9): 35-40.

YE Hairong, GE Leyi, ZHONG Guiying. Online Detection Technology of Solid Insulation RMU Based on Infrared Thermal Imaging[J]. Electric Power, 2016, 49(9): 35-40.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.2016.09.035.06

https://www.electricpower.com.cn/CN/Y2016/V49/I9/35

参考文献

[1] 赵会锋. 固体绝缘技术在高压开关设备中的应用[J]. 建筑工程技术与设计,2015（19）：235-236.
ZHAO Huifeng. Application of solid insulation technology in high voltage switch gear [J]. Architectural Engineering Technology and Besign, 2015(19): 235-236.
[2] 孙竹森,兰剑. 环保型金属封闭开关设备的技术特点与发展趋势[J]. 中国电业（技术版）,2014（6）：53-56.
SUN Zhusen, LAN Jian. Technical characteristics and development tendencies of environment-friendly switchgears[J]. China Electric Power (technology edition), 2014(6): 53-56.
[3] 付永长,张文斌,赵冲,等. 基于彩影算法的环网柜电气接头温度预报[C]//2013年中国电机工程学会年会论文集. 2013.
[4] 康利军,樊维涛. 荧光光纤测温技术在电力设备中的应用[J].中国电业（技术版）,2014（7）：23-25.
KANG Lijun, FAN Weitao. Application of fluorescence fiber temperature measurement technology in power equipment[J]. China Electric Power (Technology Edition), 2014(7): 23-25.
[5] 马继先,杨青,郭亮,等. 影响电力设备红外检测准确性因素的分析研究[J]. 华北电力技术,2012（8）：55-60.
MA Jixian, YANG Qing, GUO Liang, et al . Research on promoting the accuracy of electrical equipment diagnosing with infrared detection [J]. North China Electric Power, 2012(8): 55-60.
[6] 丁柯. 配电线路单相接地故障分析及解决措施研究[J]. 科技风,2014（17）：58.
DING Ke. Analysis of single phase grounding fault of distribution line and its solution [J]. Technology Wind, 2014(17): 58.
[7] 李文芳. 基于红外图像的电力变压器故障的在线检测[D]. 淮南：安徽理工大学,2014.
[8] 张晓东. 10 kV高压开关设备的在线测温技术探析[J]. 科技风,2014（18）：89.
ZHANG Xiaodong. On line temperature measurement technology of 10 kV high voltage switchgear [J]. Technology Wind, 2014(18): 89.
[9] 王晓刚. 电网变电设备在线监测技术要点[J]. 黑龙江科学,2014（11）：272.
WANG Xiaogang. Key points of on line monitoring technology of power grid substation equipment[J]. Heilongjiang Science, 2014(11): 272.
[10] 魏立明,杨天野. 基于图像增强和边缘检测的电力设备故障诊断研究[J]. 吉林建筑工程学院学报,2012,29（4）：84-86.
WEI Liming, YANG Tianye. Research on fault diagnosis of electrical equipment based on image enhancement and edge detection[J]. Journal of Jilin Institute of Architecture & Civil Engineering, 2012, 29(4): 84-86.
[11] 李波. 红外隐身技术的应用及发展趋势[J]. 中国光学,2013,6（6）：818-823.
LI Bo. Application and development trend of infrared stealth technology [J]. Chinese Optics, 2013, 6(6): 818-823.
[12] 夏春雷. 红外热像仪在发电厂的实际应用[J]. 科技信息,2012 （27）：391-392,432.
XIA Chunlei. The practical application of infrared thermal imaging system in power plant[J]. Science & Technology Information, 2012(27): 391-392, 432.
[13] 方攀. 红外热像技术在发动机温度测试中的应用[J]. 教育教学论坛,2012（29）：107-108.
FANG Pan. Application of infrared thermal imaging technology in engine temperature measurement [J]. Jiaoyu Jiaoxue Luntan, 2012 (29): 107-108.
[14] 刘涛,张炜,何付军,等. 红外热波检测方法图像增强环节研究[J]. 红外与激光工程,2012,41（7）：1922-1927.
LIU Tao, ZHANG Wei, HE Fujun, et al . Research on image enhancement in infrared thermal waves NDT[J]. Infrared and Laser Engineering, 2012, 41(7): 1922-1927.
[15] KOLARIC D, LIPIC T. Application of infrared thermal imaging in blade system temperature monitoring [C]//The 53rd International Symposium ELMAR. Zadar: 2011: 14-16.
[16] MEOLA C. A new approach for estimation of defects detection with infrared thermography[J]. Materials Letters, 2007, 61(3):747-750.
[17] QU Huiming. Adaptive histogram subsection modification for infrared image enhancement[C]//Society of Photo-Optical Instrumentation Engineers. Shanghai, 2006: 623310 1-7.
[18] XIE H, PIERCE L E, ULABY F. T. SAR speckle reduction using wavelet denoising and Markov random field modeling[J]. IEEE trans of Geoscience and Remote Sensing, 2002, 40(10): 2196-2212.
[19] HARRIS T R, MELAMED S. Thermal analysis and verification of a mounted monolithic integrated circuit[C]//Proceedings of the IEEE Southeast Conference. Concord, 2010: 18-21.
[20] 劳英杰. 红外热成像技术在低温绝热压力容器定期检验中的应用[J]. 化学工程与装备,2012（8）：176-178.
LAO Yingjie. Application of infrared thermal imaging technology in the periodic inspection of low temperature thermal insulation pressure vessel[J]. Chemical Engineering and Equipment, 2012(8): 176-178.
[21] GUO Jingjing, MA Lini, LI Meng. Study based on thermal infrared image [C]//International Conference on Computer Science and Network Technology, Harbin, 2011: 24-26, 80, 83.
[22] 张广燕,王俊平. PSLIP 新模型及在边缘检测和图像增强中的应用[J]. 电子学报,2015,43（2）：377-382.
ZHANG Guangyan, WANG Junping. A new PSLIP model and its application in edge detection and image enhancement[J]. Acta Electronica Sinica, 2015, 43(2): 377-382.
[23] VOROBEL R, BOTSIAN V. Parameterization method for logarithmic image processing model[C]//International Conference on Modern Problems of Radio Engineering Telecommunications and Computer Science. Ukraine, 2012: 408-408.