Identification of Plastic Deformations in Carbon Steel Elements Using the Filtered Barkhausen Noise Signal

Q4 Engineering
J. Dybała, Krzysztof Nadulicz
{"title":"Identification of Plastic Deformations in Carbon Steel Elements Using the Filtered Barkhausen Noise Signal","authors":"J. Dybała, Krzysztof Nadulicz","doi":"10.21008/J.0860-6897.2020.1.06","DOIUrl":null,"url":null,"abstract":"The paper presents new approach to processing the Barkhausen Noise signal in order to detect and identify plastic deformations in carbon steel. A new automatic method of Barkhausen effect signal filtration was investigated. Apart from a classical measurement of Barkhausen effect signal, for which the RMS value is assumed, the signal waveform factor was also used in analyzes. The developed approach to processing the Barkhausen Noise signal has made it possible to obtain more useful diagnostic data than those obtained from the raw signal.","PeriodicalId":38508,"journal":{"name":"Vibrations in Physical Systems","volume":"31 1","pages":"2020106-1-2020106-8"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vibrations in Physical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21008/J.0860-6897.2020.1.06","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

The paper presents new approach to processing the Barkhausen Noise signal in order to detect and identify plastic deformations in carbon steel. A new automatic method of Barkhausen effect signal filtration was investigated. Apart from a classical measurement of Barkhausen effect signal, for which the RMS value is assumed, the signal waveform factor was also used in analyzes. The developed approach to processing the Barkhausen Noise signal has made it possible to obtain more useful diagnostic data than those obtained from the raw signal.
利用滤波巴克豪森噪声信号识别碳钢件塑性变形
本文提出了一种处理巴克豪森噪声信号以检测和识别碳钢塑性变形的新方法。研究了一种新的巴克豪森效应信号自动滤波方法。除了对巴克豪森效应信号的经典测量假设其均方根值外,分析中还使用了信号波形因子。发展的方法来处理巴克豪森噪声信号,使它有可能获得更有用的诊断数据比那些从原始信号。
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 求助全文
来源期刊
Vibrations in Physical Systems
Vibrations in Physical Systems Engineering-Mechanics of Materials
CiteScore
0.70
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信