Electric power inspection intelligent defect detection method based on deep learning

Abstract

The invention discloses an electric power inspection intelligent defect detection method based on deep learning. The method comprises the following steps: obtaining a plurality of original images of different insulators and dividing the original images into a training set and a test set; carrying out enhancement processing on the original image of the training set to obtain an enhanced set image;dicing the original images in each enhancement set image and each test set to obtain a plurality of sub-block images and masks thereof; carrying out the semantic segmentation on each sub-block image and the mask thereof, and extracting an insulator region; obtaining a communication area of each insulator; rotating the connected region by using principal component analysis to obtain a normalized insulator image; inputting the normalized insulator image of the enhanced set image into a neural network model for training to obtain a training model; predicting insulator coordinates in the normalized insulator images of the test set through the training model; and carrying out the inverse transformation on the insulator coordinates to restore to the original image coordinates. The method can achieve the recognition and segmentation of the insulator string, is short in processing time, is high in precision, and is high in robustness.

Description

technical field [0001] The present invention relates to transmission line inspection, and more specifically, it relates to an intelligent defect detection method for electric power patrol inspection based on deep learning. Background technique [0002] Self-explosion of insulators is a common defect in high-voltage transmission lines. In order to ensure the safety and reliability of transmission lines, the power grid department needs to regularly patrol the transmission and transformation systems to investigate whether there are self-explosion insulators. The traditional inspection method is to carry out inspections manually, but this will cause problems such as high labor intensity, low work efficiency, and the personal safety of workers cannot be guaranteed. Contents of the invention [0003] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies of the prior art. The first purpose of the present invention is to provide...

AI Technical Summary

Problems solved by technology

The traditional inspection method is to conduct manual inspections, but this will cause problems such as high labor intensity, low work efficiency, and the inability to guarantee the personal safety of workers.

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