Method and device for extracting inspection key component points

Abstract

The invention provides a method and device for extracting inspection key component points, and belongs to the field of power detection, and the method for extracting the inspection key component points comprises the steps: S1, employing tower point clouds of different tower types as training samples, and determining the length of an insulator according to the different tower types and voltage levels; s2, performing vertical layering on the tower point cloud according to the insulator height, taking each layer of finely classified point cloud as a minimum learning unit of deep learning, performing model training on each unit to obtain a deep learning neural network model, and performing fine classification on tower point clouds of different tower types by utilizing the neural network model;s3, based on a fine classification result, carrying out monomerization on the tower point cloud of each tower by utilizing a model construction method; and S4, extracting the position of the component point from each monomeric model to serve as a photographing point position. By utilizing the method, the workload of manually selecting key component points can be reduced, and the working efficiency is improved.

Description

technical field [0001] The invention relates to the field of electric power detection, in particular to a method and device for extracting key component points for inspection. Background technique [0002] The power system is different from other industries. Maintenance cannot interrupt production at will. It is necessary to make sufficient predictions before the accident occurs—to solve the fault before the accident occurs, and the focus is on the preventive inspection of the transmission line. [0003] With the continuous improvement of the intelligence level of the power grid, drone inspections are increasingly used. After each inspection task is completed, a large number of inspection pictures will be generated. Under normal circumstances, the refined inspection objects of transmission lines include: (1) whether there is any defect or abnormality in the ground wire; (2) whether there is any defect or abnormality in the gold wire of the line; ) Whether there are defects...

AI Technical Summary

Problems solved by technology

[0004] Most of the existing inspection image processing methods are based on manual interpretation to complete the calibration of target components and the classification of defects. Manual interpretation is labor-intensive and low-efficiency

On the other hand, the manual interpretation method does not have a unified evaluation standard as a basis, is easily affected by personal subjective factors, and often misses or misjudges many defects; this makes the inspection effect poor, resulting in the absence of line status supervision. The effect of transmission line inspection work is greatly reduced, leaving hidden dangers to the safety of transmission lines

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