Wire strand defect detection method for transmission line

Abstract

The invention discloses a wire strand defect detection method for a transmission line. Through the method, a wire strand defect of the transmission line can be intelligently recognized. According to the wire strand defect detection method for the transmission line, an image is preprocessed; then wires are separated from a background image through image partitioning; next, feature extraction is performed on a wire image; and finally strand recognition is performed on the wires. The whole process can be automatically completed through a computer, intelligent processing of transmission line inspection data can be realized, the wire strand defect of the transmission line can be intelligently recognized, and recognition efficiency is greatly improved; and moreover, problems existing in manual observation can be greatly reduced with the efficiency, misjudgment or missing judgment caused by manual experience or working strength fatigue is avoided, overall working efficiency is improved, a fine management mode is improved, the intelligent level is raised, a large amount of manual checking time is saved, and a lot of economic investment is saved. The method is suitable for application and popularization in the technical field of image recognition.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a detection method for a wire splitting defect of a power transmission line. Background technique [0002] In the UAV inspection stage of transmission lines, the current inspection image analysis is mainly carried out manually. Super-large video and images bring a huge workload to post-analysis and processing, resulting in the status quo that the inspection analysis and report cannot be issued after the inspection of the line is completed, which is extremely unfavorable for timely grasping the operation status of the line. At the same time, the operation team needs to invest a large number of people in the inspection image analysis, and there are relatively large restrictions on the arrangement of out-of-home operations. At the same time, the results of manual-based defect analysis are easily affected by the skill level and experience of the personnel themselves, and ma...

AI Technical Summary

Problems solved by technology

Super-large video and images bring a huge workload to post-analysis and processing, resulting in the status quo that the inspection analysis and report cannot be issued after the line inspection is completed, which is extremely unfavorable for timely grasping the operation status of the line

At the same time, the operation team needs to invest a large number of people in the inspection image analysis, and there are relatively large restrictions on the arrangement of out-of-home operations. At the same time, the results of manual-based defect analysis are easily affected by the skill level and experience of the personnel themselves, and manual analysis of inspection images also reduces the Image recognition efficiency is a great waste of human resources