Research Article
Design of High Speed Railway Turnout Structural Damage Identification System Based on Machine Learning
@INPROCEEDINGS{10.1007/978-3-030-36405-2_16, author={Ailin Wang}, title={Design of High Speed Railway Turnout Structural Damage Identification System Based on Machine Learning}, proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2019}, month={11}, keywords={Machine learning High speed railway Turnout structure Damage identification System design}, doi={10.1007/978-3-030-36405-2_16} }- Ailin Wang
Year: 2019
Design of High Speed Railway Turnout Structural Damage Identification System Based on Machine Learning
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-36405-2_16
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.
