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文章摘要
基于局部区域聚类的电力设备故障区域提取方法
Region extraction of electronic fault region using local clustering algorithm
Received:January 10, 2019  Revised:January 10, 2019
DOI:10.19753/j.issn1001-1390.2020.08.008
中文关键词: Mediodshift算法, 故障区域, 红外图像, 阈值, 聚类
英文关键词: Mediodshift  fault region  infrared image  thresholding  clustering
基金项目:国家电网公司总部科技项目资助(524625160017变电设备带电运维策略及装置智能化、自动化提升技术研究与应用)
Author NameAffiliationE-mail
Feng zhengxin Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute 13995619161@139.com 
xu xiaolu Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute 13297028831@139.com 
Zhou Dongguo* Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute dgzhou1985@whu.edu.cn 
jiang yi Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute 18071045365@139.com 
Ding guocheng Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute 13297047502@139.com 
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中文摘要:
      针对电力设备红外图像诊断中热故障区域提取问题,提出了一种局部区域Mediodshift聚类的电力设备红外图像故障区域提取方法。首先,根据热故障所表现的灰度特性初始化聚类中心;然后,结合Mediodshift聚类方法,对目标区域邻域像素进行聚类。为了尽可能获取故障区域邻域相似像素,引入了基于邻域灰度的调节策略。同时,为了提高聚类效率,采用了自高向低的聚类阈值分割机制,从而使得Mediodshift算法能快速地将整幅图像中故障区域像素进行聚类,实现红外图像中热故障区域的提取。最后通过典型红外图像实验测试,验证了文中方法区域提取的有效性,且对比目前现有的一些方法,表明文中方法具有较好的故障区域提取性能。
英文摘要:
      Aiming at the problem of extracting thermal fault area in detecting power electronic using infrared imaging, a method of extracting thermal fault area is proposed, which is based on the Mediodshift with local clustering. Firstly, the clustering center is initialized according to the gray level characteristics of thermal faults. Then, the neighborhood pixels are clustered by combining Mediodshift clustering method. In order to promote the performance in clustering of pixels as far as possible, the adjustment strategy for neighborhood gray level is introduced. At the same time, in order to improve the clustering efficiency, a clustering thresholding segmentation mechanism from high to low is adopted, which enables Mediodshift algorithm to cluster the pixels of fault region quickly and to extract the thermal fault region effectively from infrared image. Finally, Experiment on some classic electronic fault images show that the region extraction performance of our method has its ability to extract the region, and is better than the performance of some existing methods.
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