A method for locating multiple parts of high-speed railway catenary based on structural reasoning network

Abstract

The invention discloses a method for locating various components of high-speed rail catenary based on a structure reasoning network. First, an image data set of high-speed catenary components is obtained, and the design structure reasoning is analyzed according to the fixed structure of the relative positional relationship of the components of the high-speed rail catenary. The feasibility of network detection; then according to the analysis conclusion, combined with the classification neural network and positioning neural network, design a structural reasoning network; finally, input the high-speed rail catenary component image data set into the reasoning network for classification training, and input new pictures to get its positioning information. The invention aims at various catenary components, improves the positioning accuracy of various catenary components, shortens the detection time and reduces the difficulty of fault detection.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a method for locating multiple components of a high-speed railway catenary based on a structural reasoning network. Background technique [0002] The catenary support and suspension device is responsible for the important task of supporting the catenary, and the condition of the device affects the stability of the entire suspension system, thereby affecting the performance of the catenary wire; when a fault occurs, the catenary wire and the pantograph may not be in good contact , which affects the quality of the flow; among them, the catenary cable base has a harsh working environment, frequent and violent vibrations, sparsely populated along the road, and difficult maintenance, which is one of the weak links of the support suspension system; Mainly, the efficiency is low; at present, some researches have been done on the detection of catenary support and suspension dev...

AI Technical Summary

Problems solved by technology

[0002] The catenary support and suspension device is responsible for the important task of supporting the catenary, and the condition of the device affects the stability of the entire suspension system, thereby affecting the performance of the catenary wire; when a fault occurs, the catenary wire and the pantograph may not be in good contact , which affects the quality of the flow; among them, the catenary cable base has a harsh working environment, frequent and violent vibrations, sparsely populated along the road, and difficult maintenance, which is one of the weak links of the support suspension system; Mainly, the efficiency is low; at present, some researches have been done on the detection of catenary support and suspension devices based on image processing. Traditional image processing is mostly for single component positioning. For example: Zhang Guinan proposed to use Harris corner detection and spectral clustering to realize the insulator anti-rotation matching; Han Ye proposed to use the local feature point matching between the catenary support suspension device image to be analyzed and the standard rotating binaural image to realize the positioning and extraction of rotating binaural ears; although deep learning can achieve multi-target positioning and The effect is improved but there are shortcomings; for example, Zhong Junping used three deep learning models to simultaneously locate 12 types of components of the high-speed rail catenary; but the experimental results show that the huge variety of different components seriously affects the detection results

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