Research On Recognition Of Key Components And Detection Of Anomaly In Transmission Line

With the development of smart grid and power system automation,computer vision technology is more and more used in intelligent inspection and online monitoring of power equipment.Transmission line breakage,foreign body,lightning flashover and so on are the key components of the transmission line(insulator,transmission tower,transmission line)is fault-frequency components,insulators blew,breakage,foreign body and other faults.The fault seriously threatens the safe and reliable operation of the transmission line.Therefore,regular monitoring of key components of transmission lines in the state,timely detection of critical problems.Through analyzing and processing the data collected from the inspection of transmission lines,it is found that the transmission line fault has become a hotspot in recent years.The main contents of this paper are as follows: 1.In the aerial image,the insulator,the transmission tower,the transmission line identification and the insulator drop fault,the power transmission tower bird 's nest fault,the transmission line foreign object hanging fault detection.Firstly,a new method based on significance detection and adaptive morphology for insulator identification and fault detection is proposed.The insulator is located by the salient algorithm of multi-feature fusion.After the insulator locating result area is divided into two parts,the adaptive morphological processing is carried out according to the proportion of the insulator area to realize the fault detection.Secondly,a new transmission tower identification method based on corner,line,color and shape features is proposed.The straight line segment and corner point in the image are extracted by LSD line segment detection and Harris corner detection respectively.The initial positioning results of the transmission tower are achieved by fusion treatment and morphological processing.Then,the HOG feature training SVM classifier is used to realize the transmission tower end.Positioning.For the nest in the transmission tower failure,the use of fusion color features,shape features to achieve accurate detection.Then,a new detection method based on line detection and parallelism is proposed for power line extraction and foreign object hanging.The transmission lines are extracted by hough line detection and parallelism determination,and the detected foreign objects are detected in the transmission line region based on the connected domain rules.Finally,the paper summarizes the work of this paper,and points out the research work that needs to be further carried out.