Rail base flaw detection and quantification based on the modal curvature method and the back propagation neural network-Reference-Cited by-同舟云学术

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Rail base flaw detection and quantification based on the modal curvature method and the back propagation neural network

Published:2022-12 Issue: Volume:142 Page:106792
ISSN:1350-6307
Container-title:Engineering Failure Analysis
language:en
Short-container-title:Engineering Failure Analysis

Author:

Liu Y.^ORCID,Li Qiutong^ORCID,Yuan Xianpu,Li Yixin,Zhu Zhehao

Publisher

Elsevier BV

Subject

General Engineering,General Materials Science

Reference41 articles.

1. Broken rail explained, 2020. https://www.networkrail.co.uk/stories/broken-rail-explained/.

2. Failure rule and statistical analysis method for U75V and U71Mn rail in service;Liu;Zhongguo Tiedao Kexue/China Railw. Sci.,2007

3. Office of Railroad Safety, Track Inspector Rail Defect Reference Manual, 2015.

4. Fracture Analysis Of Rail In A Bridge;Deng;PTCA(PART A Phys Testing),2004

5. E.E. Magel, Rolling Contact Fatigue: A Comprehensive Review, 2011.

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1. Dynamic inspection data-based analysis of rail base metal irregularities for engineering failure prevention;Engineering Failure Analysis;2024-10

2. Rail-STrans: A Rail Surface Defect Segmentation Method Based on Improved Swin Transformer;Applied Sciences;2024-04-25

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