Results 1 to 10 of about 1,502 (95)

FS-RSDD: Few-Shot Rail Surface Defect Detection with Prototype Learning [PDF]

open access: yesSensors, 2023
As an important component of the railway system, the surface damage that occurs on the rails due to daily operations can pose significant safety hazards.
Yongzhi Min   +3 more
doaj   +2 more sources

A 3D Laser Profiling System for Rail Surface Defect Detection [PDF]

open access: yesSensors, 2017
Rail surface defects such as the abrasion, scratch and peeling often cause damages to the train wheels and rail bearings. An efficient and accurate detection of rail defects is of vital importance for the safety of railway transportation. In the past few
Zhimin Xiong   +3 more
doaj   +2 more sources

RSDNet: A New Multiscale Rail Surface Defect Detection Model [PDF]

open access: yesSensors
The rapid and accurate identification of rail surface defects is critical to the maintenance and operational safety of the rail. For the problems of large-scale differences in rail surface defects and many small-scale defects, this paper proposes a rail ...
Jingyi Du   +4 more
doaj   +2 more sources

Rail surface defect data enhancement method based on improved ACGAN [PDF]

open access: yesFrontiers in Neurorobotics
Rail surface defects present a significant safety concern in railway operations. However, the scarcity of data poses challenges for employing deep learning in defect detection.
He Zhendong   +4 more
doaj   +2 more sources

Enhanced Rail Surface Defect Segmentation Using Polarization Imaging and Dual-Stream Feature Fusion [PDF]

open access: yesSensors
Rail surface defects pose significant risks to the operational efficiency and safety of industrial equipment. Traditional visual defect detection methods typically rely on high-quality RGB images; however, they struggle in low-light conditions due to ...
Yucheng Pan   +5 more
doaj   +2 more sources

An Improved Feature Pyramid Network and Metric Learning Approach for Rail Surface Defect Detection

open access: yesApplied Sciences, 2023
When deep learning methods are used to detect rail surface defects, the training accuracy declines due to small defects and an insufficient number of samples.
Zhendong He   +4 more
doaj   +1 more source

Natural Rail Surface Defect Inspection and Analysis Using 16-Channel Eddy Current System

open access: yesApplied Sciences, 2021
Trains are used as the fastest mode of transportation for both people and cargo. The train moves along a special path called “rail”, where fatigue can be accumulated due to wheel-rail contact load as a result of continuous train operation. Consistent and
Se-Gon Kwon   +4 more
doaj   +1 more source

Rail Surface Defect Detection Based on An Improved YOLOv5s

open access: yesApplied Sciences, 2023
As the operational time of the railway increases, rail surfaces undergo irreversible defects. Once the defects occur, it is easy for them to develop rapidly, which seriously threatens the safe operation of trains.
Hui Luo, Lianming Cai, Chenbiao Li
doaj   +1 more source

Detection of Surface Defects on Railway Tracks Based on Deep Learning

open access: yesIEEE Access, 2022
The detection of rail surface defects is very important in railway transportation. However, the edge defects on both sides of the rail and the multi-scale variation between different types of defects both pose challenges to the detection of rail surface ...
Maoli Wang   +3 more
doaj   +1 more source

Thermal non-destructive characterization of rail networks by using Infrared Thermography and FEM simulation [PDF]

open access: yesMATEC Web of Conferences, 2022
Because of the repeated passage of trains, anomalies are created inside the rails in the form of cracks of different shapes and position. These are due essentially to the wheel – rail contact. They present a hazard causing at the final stage rail failure,
Noufid Abdelhamid   +4 more
doaj   +1 more source

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