A method and system for intelligent identification of electrical equipment defects based on UAV inspection images

Abstract

The present invention relates to a method and system for intelligent identification of defects in power equipment based on unmanned aerial vehicle inspection images. The characteristics are integrated and analyzed to realize the automatic positioning and identification of typical parts, and the corresponding defect analysis of typical parts is carried out according to the set defect identification rules to realize the analysis and identification of common defects; the analysis and identification results are summarized, analyzed and processed according to Classification of component types, defect types, and defect levels facilitates classification and query based on requirements, and partial enlarged display of specific components. The present invention can effectively tap the huge value of unstructured big data in power grid inspection, refine the inspection operation process, and play an important role in ensuring the stable operation of transmission lines.

Description

technical field [0001] The invention relates to the technical field of electric power system and image processing, in particular to a method and system for intelligently identifying defects of electric power equipment based on drone inspection images. Background technique [0002] With the interconnection of large power grids and the continuous expansion of the scale of the power grid, the security and stability of the power grid operation has attracted widespread attention. On the one hand, grassroots line inspection work is often organized with reference to operational experience. However, with the continuous change of the line operating environment, the operating experience is also constantly changing. On the other hand, with the continuous extension of the operating lines, the contradiction between the increase in line inspection workload and the shortage of line inspection personnel has become increasingly prominent. Therefore, the realization of fine line inspection ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the technical problems existing in the prior art, the present invention provides an intelligent identification method and system for electric equipment defects based on drone inspection images, and starts from the unstructured big data of full-spectrum inspection images of power transmission lines to study power transmission A method for automatically analyzing and diagnosing transmission line defects and hidden dangers by means of on-site line images, videos, infrared thermal images, and ultraviolet imaging, using helicopters (drones) to automatically inspect and collect images, videos, infrared thermal imaging, ultraviolet imaging, etc. The image characteristics of the power equipment are analyzed in depth, and the image preprocessing technology is selected to process the acquired image, including denoising, enhancement, restoration, super-resolution reconstruction, registration, etc., and then the features of the power equipment and its fault images are extracted. Establish a typical fault image library by using typical defect experimental image samples and on-site image samples, and effectively judge the main abnormalities and defects of transmission lines and their operating environment, such as the appearance defects of transmission lines, through the learning and training of feature models, and develop a defect hidden danger analysis visualization system

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