Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Infrared》 2018-01
Add to Favorite Get Latest Update

Detection Method of Arrester Fault Based on Infrared Images

LU Bin;ZHU Hai-feng;GU Zhen-fu;GAO Guan-qun;LI Jia-jun;LI Shi-chang;YAO Qiang;Heibei Zhanghewan Energy Storage Power Generation Co Ltd;Key Laboratory of Polarization Imaging Detection Technology in Anhui Province;School of Electronics and Information Engineering,Anhui University;  
In power systems,to use computer vision and image processing technologies to detect the faults in arresters plays an important role in their safe operation.An arrester fault detection method based on infrared images is proposed.The algorithm firstly preprocesses the input images and uses Scale-Invariant Feature Transform(SIFT)descriptors and K-means~(++)algorithm to train a vision dictionary to precisely position the arrester.Then,it uses Linear Spectral Clustering(LSC)to segment the area selected.Finally,it implements the detection of arrester fault by analyzing the characteristics in the thermal image of the arrester.The experimental results show that the proposed algorithm can detect the faults in arresters effectively.
【Fund】: 国家自然科学基金项目(61501003);; 国家电网公司科技项目(5212D01502DB);; 偏振光成像探测技术安徽省重点实验室开放课题(2016-KFJJ-002)
【CateGory Index】: TM862;TP391.41
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved