COQTEL project dataset : Corrosion quantification trough extended use of Lamb waves

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2025-04-01 Epub Date: 2025-02-13 DOI:10.1016/j.dib.2025.111393
C. Nicard , M. Rébillat , O. Devos , M. El May , F. Letellier , S. Dubent , M. Thomachot , M. Fournier , P. Masse , N. Mechbal
{"title":"COQTEL project dataset : Corrosion quantification trough extended use of Lamb waves","authors":"C. Nicard ,&nbsp;M. Rébillat ,&nbsp;O. Devos ,&nbsp;M. El May ,&nbsp;F. Letellier ,&nbsp;S. Dubent ,&nbsp;M. Thomachot ,&nbsp;M. Fournier ,&nbsp;P. Masse ,&nbsp;N. Mechbal","doi":"10.1016/j.dib.2025.111393","DOIUrl":null,"url":null,"abstract":"<div><div>Corrosion poses significant safety and cost challenges in the aeronautic industry. Ultrasonic Lamb Waves (LW), emitted and received by a sparse array of piezoelectric elements (PZT), offer an efficient, cost-effective, and versatile solution for corrosion monitoring. This dataset corresponds to two experiments involving a LW solution based on a sparse PZT array and able to monitor corrosion pit growth on a 316L stainless steel plate during controlled corrosion. The corrosion pit size is electrochemically controlled by the imposed electrical potential and the injection of a corrosive NaCl solution through a capillary at the desired pit location. Simultaneously, the corrosion pit growth is monitored in-situ every 10 seconds using a sparse array of 4 PZTs bonded to the back of the steel plate. Two independent experiments were conducted to assess the repeatability of this approach. The collected dataset collected can facilitate the development of Structural Health Monitoring (SHM) algorithms and methodologies, provide data for waves/damage interaction modeling, and help bridging the gap between research and industry in this domain.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111393"},"PeriodicalIF":1.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340925001258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/13 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Corrosion poses significant safety and cost challenges in the aeronautic industry. Ultrasonic Lamb Waves (LW), emitted and received by a sparse array of piezoelectric elements (PZT), offer an efficient, cost-effective, and versatile solution for corrosion monitoring. This dataset corresponds to two experiments involving a LW solution based on a sparse PZT array and able to monitor corrosion pit growth on a 316L stainless steel plate during controlled corrosion. The corrosion pit size is electrochemically controlled by the imposed electrical potential and the injection of a corrosive NaCl solution through a capillary at the desired pit location. Simultaneously, the corrosion pit growth is monitored in-situ every 10 seconds using a sparse array of 4 PZTs bonded to the back of the steel plate. Two independent experiments were conducted to assess the repeatability of this approach. The collected dataset collected can facilitate the development of Structural Health Monitoring (SHM) algorithms and methodologies, provide data for waves/damage interaction modeling, and help bridging the gap between research and industry in this domain.
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
COQTEL项目数据集:通过扩展使用兰姆波进行腐蚀量化
腐蚀对航空工业的安全和成本提出了重大挑战。超声波兰姆波(LW)由稀疏的压电元件阵列(PZT)发射和接收,为腐蚀监测提供了一种高效、经济、通用的解决方案。该数据集对应于两个实验,涉及基于稀疏PZT阵列的LW解决方案,并能够在受控腐蚀期间监测316L不锈钢板上的腐蚀坑生长。腐蚀坑的大小由施加的电势和通过毛细管在期望的坑位置注入腐蚀性NaCl溶液的电化学控制。同时,利用粘接在钢板背面的4个PZTs稀疏阵列,每10秒对腐蚀坑的生长情况进行现场监测。进行了两个独立的实验来评估这种方法的可重复性。收集到的数据集可以促进结构健康监测(SHM)算法和方法的发展,为波浪/损伤相互作用建模提供数据,并有助于弥合该领域研究与工业之间的差距。
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
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
期刊最新文献
VisioDECT: A robust dataset for aerial and scenario based multi-drone detection, identification, and neutralization 100 m climate and heat stress data up to 2100 for 142 cities around the globe Measurement data from full-scale fire experiments of battery electric vehicles and internal combustion engine vehicles Dataset of in-situ meteorological measurements for urban wind energy assessment in the southern region of the Dominican Republic Survey data on students’ perceptions, knowledge, and use of learning analytics (LA) and generative artificial intelligence (GenAI) for the personalization of learning
×
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:604180095
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