Design of High Speed Railway Turnout Structural Damage Identification System Based on Machine Learning

Abstract

In order to improve the damage detection and identification ability of high-speed railway turnout structure, a machine learning-based damage identification method for high-speed railway turnout structure is proposed, and the computer vision image analysis method is used to detect the damage of high-speed railway turnout structure. The super-linear segmentation and feature recognition of the damaged parts of high-speed railway turnout structures are realized by means of active contour detection, and the feature segmentation and localization of high-speed railway turnout structures are carried out in the damaged areas. According to the result of feature matching, the machine learning algorithm is used to identify the damage of high-speed railway turnout structure. The simulation results show that the accuracy of the proposed method for damage identification of high-speed railway turnout structure is high, and the ability of damage detection and identification of high-speed railway turnout structure is stronger than that of high-speed railway turnout structure.