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   Articles with "rail surface" as a keyword



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Determination of temperature stresses in CWR based on measured rail surface temperatures

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recommendations! Published in 2021 at "Construction and Building Materials"

DOI: 10.1016/j.conbuildmat.2021.122713

Abstract: Abstract The main aim of conducted research is determination of temperature stresses due to the uneven temperature distribution in CWR. This paper presents a methodology for determination of temperature stresses in CWR based on (1)… read more here.

Keywords: temperature; temperature stresses; determination temperature; rail surface ... See more keywords
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Visual quantitative detection of rail surface crack based on laser ultrasonic technology

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recommendations! Published in 2021 at "Optik"

DOI: 10.1016/j.ijleo.2021.166732

Abstract: Abstract The surface rolling contact fatigue crack is a common crack on the rail surface. When it extends to a certain length, it will lead to rail fracture and affect the safety of railway operation.… read more here.

Keywords: surface; crack; quantitative detection; rail surface ... See more keywords

Couple of biomimetic surfaces with different morphologies for remanufacturing nonuniform wear rail surface

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recommendations! Published in 2018 at "Optics and Laser Technology"

DOI: 10.1016/j.optlastec.2017.09.020

Abstract: Abstract In this work, biomimetic laser treatment was performed on repairing and remanufacturing the nonuniform worn rail surface. The wearing depth distribution of three work regions of a failure rail surface was discussed, and different thickness hardening layers with different… read more here.

Keywords: remanufacturing nonuniform; rail surface; surface; surfaces different ... See more keywords

Rail surface damage management through monitoring and modelling

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recommendations! Published in 2024 at "International Journal of Rail Transportation"

DOI: 10.1080/23248378.2024.2337364

Abstract: ABSTRACT Rolling contact fatigue (RCF) cracking and wear significantly impact rail surfaces. The interaction between them is crucial; wear dominance can remove initiated cracks, while low wear rates may escalate crack propagation, elevating rail failure… read more here.

Keywords: damage management; rail surface; rail; monitoring ... See more keywords

3D reconstruction and depth estimation method for local anomalies of rail surface based on multi-view stereo matching

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recommendations! Published in 2024 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ad83e8

Abstract: Detecting rail surface anomalies has become crucial for ensuring the safety of train operations. However, manual detection methods are time-consuming and labor-intensive. Although traditional detection models based on one-dimensional signals or two-dimensional images can effectively… read more here.

Keywords: rail surface; depth; surface; estimation ... See more keywords

A lightweight rail surface defect detection algorithm integrating multi-attention mechanism and content-aware reassembly of features

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recommendations! Published in 2025 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/adfe08

Abstract: Rail surface defect inspection and maintenance play a crucial role in ensuring the safety of railway operations. While existing deep learning-based lightweight detection methods have enhanced the efficiency of manual inspections, their performance remains less… read more here.

Keywords: detection; surface defect; rail surface; content aware ... See more keywords

A Multi-Modal Approach to Rail Surface Condition Analysis: The MFDF-Net

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3427347

Abstract: Surface defects on the track may lead to accidents and pose a serious threat to the safety of passengers and staff. Regarding current detection methods, there are still shortcomings: manual detection is time-consuming and labor-intensive;… read more here.

Keywords: surface condition; rail surface; surface; multi modal ... See more keywords

Research on Real-Time Detection System of Rail Surface Defects Based on Deep Learning

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recommendations! Published in 2024 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2024.3402730

Abstract: The heavy workload of rail track inspection makes it time consuming, and thus calls out a real-time inspection algorithm to achieve precise and efficient detection. In this study, we developed a real-time detection system for… read more here.

Keywords: detection; system; real time; time ... See more keywords

RGB-D Rail Surface Defect Inspection Driven by Conditional Diffusion Architecture and Frequency Knowledge

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recommendations! Published in 2025 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2025.3554715

Abstract: RGB-D rail surface defect inspection (RSDI) is a critical measure for ensuring transportation safety. It improves inspection accuracy by using depth maps, but the issue of poor-quality depth maps in rail defect datasets is often… read more here.

Keywords: surface defect; rail surface; rgb; inspection ... See more keywords

Deep Learning and Machine Vision-Based Inspection of Rail Surface Defects

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recommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2021.3138498

Abstract: Surface defects are usually the early phenomenon of rail failure, which threatens the safety of railroad transportation critically, and the timely detection of surface defects helps to eliminate the potential risk of rail and reduce… read more here.

Keywords: surface defects; rail surface; surface; learning machine ... See more keywords

Deep Learning and Laser-Based 3-D Pixel-Level Rail Surface Defect Detection Method

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recommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2023.3272033

Abstract: 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. However, the scale and harsh… read more here.

Keywords: pixel level; rail surface; surface; defect detection ... See more keywords