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Deep Learning and Laser-Based 3-D Pixel-Level Rail Surface Defect Detection Method
IEEE Transactions on Instrumentation and Measurement, 2023 Rail surface defect inspection is of particular importance in modern railways. Accurate and efficient surface defect detection approaches support optimized maintenance. This enables the safe operation of the railway network.
Jiaqi Ye, Edward Stewart, Qianyu Chen
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Rail surface defect detection based on improved Mask R-CNN
Computers and Electrical Engineering, 2022Hao Wang, Mengjiao Li, Zhibo Wan
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Detection for Rail Surface Defects via Partitioned Edge Feature
IEEE Transactions on Intelligent Transportation Systems, 2022Visual inspection techniques for rail surface defects have become prevalent approaches to obtain information on rail surface damage. However, uneven illumination leads to illegibility of local information, and the change of the wheel-rail area results in the changeful background of the rail surface, both of which pose challenges to the visual ...
Xuefeng Ni +4 more
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A Visual Detection System for Rail Surface Defects
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2012Discrete surface defects are the most common anomalies of rails and they should be carefully inspected. However, it is a challenge to detect such defects in a vision system because of illumination inequality and the variation of reflection property of rail surfaces.
Qingyong Li, Shengwei Ren
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Morphological Detection and Extraction of Rail Surface Defects
IEEE Transactions on Instrumentation and Measurement, 2020Rail inspection by means of a visual system has been a subject of a number of publications in recent years. The main requirements with regard to such a system are that it has to be fast, nondestructive, and accurate. This article presents a system for rail defect detection and shape extraction utilizing morphological operations.
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Deep convolutional neural networks for detection of rail surface defects
2016 International Joint Conference on Neural Networks (IJCNN), 2016In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings. This huge amount of data makes it impossible to manually inspect the images and detect rail surface defects. Therefore, automated detection
Shahrzad Faghih-Roohi +4 more
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An Algorithm for the Detection and Measurement of Rail Surface Defects
Journal of the American Statistical Association, 1993Abstract Defects on the surface of railroad tracks have been the cause of growing concern over the past three decades. The automated detection and classification of rail surface defects would be of great assistance to rail maintenance planners, who develop grinding strategies to prevent the development of potentially dangerous deterioration. Videotaped
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Defect detection on rail surfaces by a vision based system
IEEE Intelligent Vehicles Symposium, 2004, 2004A new vision based inspection technique for rail surface defects is presented. It replaces visual checks with an automatic inspection system. Colour line-scan cameras and a special image acquisition method- the so called spectral image differencing procedure (SIDP- allow the automatic detection of defects on rail surfaces, like flakes, cracks, grooves ...
E. Deutschl +3 more
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Defect detection in rails using ultrasonic surface waves
Insight - Non-Destructive Testing and Condition Monitoring, 2007Defects in rails caused by rolling contact fatigue (RCF) are of growing concern to the railway industry. Conventional ultrasonic inspection methods are often not reliable in detecting critical RCF defects. The aim of this work was to develop a reliable screening tool that discriminates between critical and tolerable defects and therefore complements ...
D Hesse, P Cawley
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RMSDNet: A Lightweight Object Detection Network for Rail Surface Defect
IEEE Transactions on Instrumentation and MeasurementYuejian Chen +4 more
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