An Improved Target Network Model for Rail Surface Defect Detection
Applied SciencesRail surface defects typically serve as early indicators of railway malfunctions, which may compromise the quality and corrosion resistance of rails, thereby endangering the safe operation of trains. The timely detection of defects is essential to ensure
Ye Zhang +4 more
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Rail-STrans: A Rail Surface Defect Segmentation Method Based on Improved Swin Transformer
Applied SciencesWith the continuous expansion of the transport network, the safe operation of high-speed railway rails has become a crucial issue. Defect detection on the surface of rails is a key part of ensuring the safe operation of trains.
Chenghao Si +3 more
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Rail Surface Defect Diagnosis Based on Image–Vibration Multimodal Data Fusion
Big Data and Cognitive ComputingTo address the challenges in existing multi-sensor data fusion methods for rail surface defect diagnosis, particularly their limitations in fully exploiting potential synergistic information among multimodal data and effectively bridging the semantic gap
Zhongmei Wang +4 more
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An Improved YOLOv8 Algorithm for Rail Surface Defect Detection
IEEE AccessTo tackle the issues raised by detecting small targets and densely occluded targets in railroad track surface defect detection, we present an algorithm for detecting defects on railroad tracks based on the YOLOv8 model.
Yan Wang +3 more
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Rail Surface Defect Detection Based on Dual-Path Feature Fusion
ElectronicsWith the rapid development of rail transit, the workload of track maintenance has increased, making the intelligent identification of rail surface defects crucial for improving detection efficiency. To address issues such as low defect detection accuracy,
Yinfeng Zhong, Guorong Chen
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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 +3 more
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Thermal non-destructive characterization of rail networks by using Infrared Thermography and FEM simulation [PDF]
MATEC 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
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A Study on Railway Surface Defects Detection Based on Machine Vision
Entropy, 2021 The detection of rail surface defects is an important tool to ensure the safe operation of rail transit. Due to the complex diversity of track surface defect features and the small size of the defect area, it is difficult to obtain satisfying detection ...
Tangbo Bai +3 more
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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 +5 more
doaj +1 more source
An initial investigation on the potential applicability of Acoustic Emission to rail track fault detection. [PDF]
, 2004 In light of recent accidents in the rail industry, the assessment of the mechanical integrity of rail-track is of vital importance. This encompasses the integrity of the track due to rolling contact fatigue and surface wear. Whilst numerous techniques
Mba, David, Bruzelius, Kristoffer
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