Research On Insulator Identification And Fault State Detection Technology Of Transmission Line

The transmission lines are complex during operation,and the insulator act as an important component,there are many kinds and huge amounts.As the insulators are located in the wild environment,they are easily affected by external weather conditions,own manufacturing processes,human factors,etc.,which could inevitably occur some problems such as the self-shattering,the cracking,the contamination,etc.,Because these defects will difficultly ensure the safe and stable operation of transmission lines.,Therefore,it is very important to detect and identify the fault states of insulators in transmission lines.With the continuous advancement of the “strong smart grid” and the development of computer vision and image processing technology,the intelligent monitoring technology for transmission lines has been realized.In this paper,based on processing technology above,the automatic identification and extraction algorithms of insulators under complex background and uneven illumination are mainly studied.In addition,aiming at the three common fault states of insulators,the suitable identification and diagnosis algorithms are designed for the actual field conditions.Finally,through insulator fault status recognition and diagnosis system of the transmission line,the designed methods are tested and verified.The work of this paper mainly includes the following aspects:(1)According to introduce the current research status,existing problems and development prospects of insulators identification and fault status detection in the transmission line,a research plan is proposed in this paper.Then,the used insulator identification key technologies are also introduced.(2)In view of shadows or dark regions of composite insulator surface under the condition of natural light,insulator cannot be accurately segmented.A kind of composite insulator images segmentation method based on improved color difference is presented.Firstly,the image is compensated by the local-based pixel illumination homomorphism compensation method.Then,the color components of the image are extracted and analyzed.Finally,the optimal color difference gray-scale image is obtained by the improved color difference method,then,the insulator is segmented and recognized.Compared with other methods,this method is better than other methods.(3)This paper analyzes and studies the three common fault conditions of insulators,focusing on the “self-shattering” of insulators,an automatic identification and localization technology of self-shattered glass insulators based on LBP texture features is proposed.Then,a series of experiments are designed to verify the effectiveness of the algorithm.The accuracy of the proposed method is as high as 90.63%,which is much higher than other shape-based,edge-based detection methods.Meanwhile,the detection and identification of insulator icing,surface cracking and contamination faults are also further studied.(4)The overall architecture and software platform of the fault state identification and diagnosis system for transmission line insulators are briefly introduced.The on-site insulator images are collected on this platform and then the detection are carried out.The result is satisfactory through field installation test.