Image Recognition And Classification Of Transmission Line Insulator Defects System Application Research

With the application of drones in power systems,the daily inspection of transmission lines also collects insulator image data through drones.This inspection method will generate a large amount of image data.It is necessary to find defects in these image data.Insulator.At present,the method of relying on on-site maintenance personnel to manually search for insulator images taken by a large number of drones is inefficient and expensive;Therefore,a system for quickly recognizing and classifying the image data collected by the drone is needed to screen out the pictures of defective insulators,quickly locate the position of the insulator defects,and repair and replace the defective insulators more quickly to ensure safe and stable operation of the power grid.In order to study how to realize the recognition and classification of insulator defect images,this paper introduces the development status of image recognition technology,and analyzes the application examples of image recognition technology at home and abroad and the application status in power systems;It also elaborates the types of insulators currently used in power transmission lines,and what types of defects each type of insulator will appear and the manifestations of these defects;at the same time,it also introduces the shooting methods and the results obtained when shooting insulators with drones Image data format and characteristics.This paper proposes a set of specific procedures for the identification of insulator defects.First,a sample library of insulator defect images is established as a comparison object,and then the insulator images to be identified are processed,mainly gray-scale processing and image segmentation,and then the insulators in the image The contour and gray value feature elements are extracted,and finally,the extracted insulator image feature elements are matched with the insulator image data in the sample library to realize the identification and classification of the insulator tour image.In this paper,through the MVC design model of Javaweb,using the Java language combined with open CV vision library and server,database and other tools to design and realize the insulator defect image recognition classification system,this system mainlyincludes insulator defect image sample management module,insulator image management Module and insulator image recognition result management module;which mainly realizes the import and editing of sample pictures and the import and defect recognition of insulator images to be inspected;and the export of defect recognition results.At the same time,by importing the collected sample pictures and the specific pictures to be tested,analyze the defect identification results of this system to verify that the system can perform insulator image recognition on the defects in the sample library.With the promotion of UAV autonomous driving and the increase in the amount of inspection data,data analysis and processing also need to be further developed.The research result of this topic is to analyze the image data of transmission line inspections,which not only adapts to the future development of digital power grids.It can also reduce manpower input to a certain extent and improve the efficiency of daily power production and inspection.