Results 1 to 10 of about 255 (66)

A 3D Laser Profiling System for Rail Surface Defect Detection

Sensors, 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, Qingquan Li, Qingzhou Mao   +2 more
exaly   +3 more sources

Rail Surface Defect Detection Based on An Improved YOLOv5s

Applied Sciences (Switzerland), 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
exaly   +3 more sources

RSDNet: A New Multiscale Rail Surface Defect Detection Model

Sensors
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
exaly   +3 more sources

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

Applied 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, Taek-Gyu Lee, Sang-Jun Park, Jeong-Won Park, Jong-Min Seo   +4 more
doaj   +1 more source

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

Sensors, 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, Ziwei Wang, Yang Liu, Zheng Wang   +3 more
doaj   +1 more source

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

Applied 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, Shiju Ge, Yan He, Jie Liu, Xiaoyu An   +4 more
doaj   +1 more source

Codiing system for rail defects in accordance with IRS 70712 [PDF]

Tehnika, 2021
Rail defects due to the rolling contact fatigue have a significant place in the Handbook of Rail Defects in the framework of UIC Code 712 in 2002. The paper presents the system for coding and classification of rail defects according to UIC recommendation
Popović Zdenka J., Lazarević Luka M., Mićić Milica M., Brajović Ljiljana M.   +3 more
doaj   +1 more source

Ensemble model for rail surface defects detection.

PLoS ONE, 2022
The detection of rail surface defects is vital for high-speed rail maintenance and management. The CNN-based computer vision approach has been proved to be a strong detection tool widely used in various industrial scenarios.
Hailang Li, Fan Wang, Junbo Liu, Haoran Song, Zhixiong Hou, Peng Dai   +5 more
doaj   +1 more source

Detection of Surface Defects on Railway Tracks Based on Deep Learning

IEEE 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, Kaizhi Li, Xiao Zhu, Yining Zhao   +3 more
doaj   +1 more source

Feature Augmentation Based on Pixel-Wise Attention for Rail Defect Detection

Applied Sciences, 2022
Image-based rail defect detection could be conceptually defined as an object detection task in computer vision. However, unlike academic object detection tasks, this practical industrial application suffers from two unique challenges, including object ...
Hongjue Li, Hailang Li, Zhixiong Hou, Haoran Song, Junbo Liu, Peng Dai   +5 more
doaj   +1 more source