An investigation on rail health monitoring using acoustic emission technique by tensile test

Xin Zhang, Naizhang Feng, Zhongxian Zou, Yan Wang, Yi Shen
{"title":"An investigation on rail health monitoring using acoustic emission technique by tensile test","authors":"Xin Zhang, Naizhang Feng, Zhongxian Zou, Yan Wang, Yi Shen","doi":"10.1109/I2MTC.2015.7151415","DOIUrl":null,"url":null,"abstract":"In order to detect the health status of high-speed railway, various studies have been examined by Acoustic Emission (AE) method. However, little work has been done on studying the relationship between rail status and features of AE signals, and this relationship can be used to establish a detection criterion for rail health monitoring. This paper presents a methodology on rail health monitoring by AE signals and establishing a detection criterion. AE signals in different safe status are obtained by tensile testing machine and AE data acquisition system. The safe and unsafe region of rail steel is analyzed by stress-strain curve. Based on the Chebyshev's inequality and the variation rate of AE hits, a detection criteria is established to detect the safe status of rail, and the corresponding detection procedure are provided. The results clearly illustrate that the proposed method can detect the safe status of rail effectively.","PeriodicalId":424006,"journal":{"name":"2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2MTC.2015.7151415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

In order to detect the health status of high-speed railway, various studies have been examined by Acoustic Emission (AE) method. However, little work has been done on studying the relationship between rail status and features of AE signals, and this relationship can be used to establish a detection criterion for rail health monitoring. This paper presents a methodology on rail health monitoring by AE signals and establishing a detection criterion. AE signals in different safe status are obtained by tensile testing machine and AE data acquisition system. The safe and unsafe region of rail steel is analyzed by stress-strain curve. Based on the Chebyshev's inequality and the variation rate of AE hits, a detection criteria is established to detect the safe status of rail, and the corresponding detection procedure are provided. The results clearly illustrate that the proposed method can detect the safe status of rail effectively.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
拉伸试验声发射技术在钢轨健康监测中的应用研究
为了检测高速铁路的健康状况,各种研究都采用声发射(AE)方法进行检测。然而,对钢轨状态与声发射信号特征之间关系的研究很少,这种关系可以用来建立钢轨健康监测的检测准则。本文提出了一种利用声发射信号进行轨道健康监测的方法,并建立了检测准则。通过拉伸试验机和声发射数据采集系统获取不同安全状态下的声发射信号。利用应力-应变曲线分析了钢轨钢的安全与不安全区域。基于切比雪夫不等式和声发射命中变化率,建立了检测钢轨安全状态的检测准则,并给出了相应的检测程序。结果表明,该方法能有效地检测钢轨的安全状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Toward a unified framework for static and dynamic measurements High Throughput Screening System for screening of 3D cell cultures An improved spectral approach to estimate the integral non-linearity of analog-to-digital converters Rail health monitoring using acoustic emission technique based on NMF and RVM Digital system for monitoring volcanic seismicity
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1