Review on Rail Damage Detection Technologies for High-Speed Trains

From the point of view of the intelligent operation and maintenance of high-speed train tracks, this paper examines the research status of high-speed train rail damage detection technology in the field of high-speed train track operation and maintenance detection in recent years, summarizes the dama...

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Main Authors: Yu Wang, Bingrong Miao, Ying Zhang, Zhong Huang, Songyuan Xu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/14/7725
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author Yu Wang
Bingrong Miao
Ying Zhang
Zhong Huang
Songyuan Xu
author_facet Yu Wang
Bingrong Miao
Ying Zhang
Zhong Huang
Songyuan Xu
author_sort Yu Wang
collection DOAJ
description From the point of view of the intelligent operation and maintenance of high-speed train tracks, this paper examines the research status of high-speed train rail damage detection technology in the field of high-speed train track operation and maintenance detection in recent years, summarizes the damage detection methods for high-speed trains, and compares and analyzes different detection technologies and application research results. The analysis results show that the detection methods for high-speed train rail damage mainly focus on the research and application of non-destructive testing technology and methods, as well as testing platform equipment. Detection platforms and equipment include a new type of vortex meter, integrated track recording vehicles, laser rangefinders, thermal sensors, laser vision systems, LiDAR, new ultrasonic detectors, rail detection vehicles, rail detection robots, laser on-board rail detection systems, track recorders, self-moving trolleys, etc. The main research and application methods include electromagnetic detection, optical detection, ultrasonic guided wave detection, acoustic emission detection, ray detection, vortex detection, and vibration detection. In recent years, the most widely studied and applied methods have been rail detection based on LiDAR detection, ultrasonic detection, eddy current detection, and optical detection. The most important optical detection method is machine vision detection. Ultrasonic detection can detect internal damage of the rail. LiDAR detection can detect dirt around the rail and the surface, but the cost of this kind of equipment is very high. And the application cost is also very high. In the future, for high-speed railway rail damage detection, the damage standards must be followed first. In terms of rail geometric parameters, the domestic standard (TB 10754-2018) requires a gauge deviation of ±1 mm, a track direction deviation of 0.3 mm/10 m, and a height deviation of 0.5 mm/10 m, and some indicators are stricter than European standard EN-13848. In terms of damage detection, domestic flaw detection vehicles have achieved millimeter-level accuracy in crack detection in rail heads, rail waists, and other parts, with a damage detection rate of over 85%. The accuracy of identifying track components by the drone detection system is 93.6%, and the identification rate of potential safety hazards is 81.8%. There is a certain gap with international standards, and standards such as EN 13848 have stricter requirements for testing cycles and data storage, especially in quantifying damage detection requirements, real-time damage data, and safety, which will be the key research and development contents and directions in the future.
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publishDate 2025-07-01
publisher MDPI AG
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series Applied Sciences
spelling doaj-art-4d9b34fbb3fb4feaaf33ec04e1fed0882025-08-20T03:58:26ZengMDPI AGApplied Sciences2076-34172025-07-011514772510.3390/app15147725Review on Rail Damage Detection Technologies for High-Speed TrainsYu Wang0Bingrong Miao1Ying Zhang2Zhong Huang3Songyuan Xu4State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, ChinaState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, ChinaFrom the point of view of the intelligent operation and maintenance of high-speed train tracks, this paper examines the research status of high-speed train rail damage detection technology in the field of high-speed train track operation and maintenance detection in recent years, summarizes the damage detection methods for high-speed trains, and compares and analyzes different detection technologies and application research results. The analysis results show that the detection methods for high-speed train rail damage mainly focus on the research and application of non-destructive testing technology and methods, as well as testing platform equipment. Detection platforms and equipment include a new type of vortex meter, integrated track recording vehicles, laser rangefinders, thermal sensors, laser vision systems, LiDAR, new ultrasonic detectors, rail detection vehicles, rail detection robots, laser on-board rail detection systems, track recorders, self-moving trolleys, etc. The main research and application methods include electromagnetic detection, optical detection, ultrasonic guided wave detection, acoustic emission detection, ray detection, vortex detection, and vibration detection. In recent years, the most widely studied and applied methods have been rail detection based on LiDAR detection, ultrasonic detection, eddy current detection, and optical detection. The most important optical detection method is machine vision detection. Ultrasonic detection can detect internal damage of the rail. LiDAR detection can detect dirt around the rail and the surface, but the cost of this kind of equipment is very high. And the application cost is also very high. In the future, for high-speed railway rail damage detection, the damage standards must be followed first. In terms of rail geometric parameters, the domestic standard (TB 10754-2018) requires a gauge deviation of ±1 mm, a track direction deviation of 0.3 mm/10 m, and a height deviation of 0.5 mm/10 m, and some indicators are stricter than European standard EN-13848. In terms of damage detection, domestic flaw detection vehicles have achieved millimeter-level accuracy in crack detection in rail heads, rail waists, and other parts, with a damage detection rate of over 85%. The accuracy of identifying track components by the drone detection system is 93.6%, and the identification rate of potential safety hazards is 81.8%. There is a certain gap with international standards, and standards such as EN 13848 have stricter requirements for testing cycles and data storage, especially in quantifying damage detection requirements, real-time damage data, and safety, which will be the key research and development contents and directions in the future.https://www.mdpi.com/2076-3417/15/14/7725track railintelligent operation and maintenancenon-destructive testingintelligencelife prediction
spellingShingle Yu Wang
Bingrong Miao
Ying Zhang
Zhong Huang
Songyuan Xu
Review on Rail Damage Detection Technologies for High-Speed Trains
Applied Sciences
track rail
intelligent operation and maintenance
non-destructive testing
intelligence
life prediction
title Review on Rail Damage Detection Technologies for High-Speed Trains
title_full Review on Rail Damage Detection Technologies for High-Speed Trains
title_fullStr Review on Rail Damage Detection Technologies for High-Speed Trains
title_full_unstemmed Review on Rail Damage Detection Technologies for High-Speed Trains
title_short Review on Rail Damage Detection Technologies for High-Speed Trains
title_sort review on rail damage detection technologies for high speed trains
topic track rail
intelligent operation and maintenance
non-destructive testing
intelligence
life prediction
url https://www.mdpi.com/2076-3417/15/14/7725
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AT yingzhang reviewonraildamagedetectiontechnologiesforhighspeedtrains
AT zhonghuang reviewonraildamagedetectiontechnologiesforhighspeedtrains
AT songyuanxu reviewonraildamagedetectiontechnologiesforhighspeedtrains