Multi-type damage localization using the scattering coefficient-based RAPID algorithm with damage indexes separation and imaging fusion

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY Structural Health Monitoring-An International Journal Pub Date : 2023-08-10 DOI:10.1177/14759217231191267
Qiao Bao, Tian Xie, Weiwei Hu, Kai Tao, Qiang Wang
{"title":"Multi-type damage localization using the scattering coefficient-based RAPID algorithm with damage indexes separation and imaging fusion","authors":"Qiao Bao, Tian Xie, Weiwei Hu, Kai Tao, Qiang Wang","doi":"10.1177/14759217231191267","DOIUrl":null,"url":null,"abstract":"Guided waves-based structural health monitoring (SHM) methods have potential for practical applications, since they are sensitive to small damages and are able to realize large area monitoring. Among these methods, the Reconstruction Algorithm for Probabilistic Inspection (RAPID), using a Piezoelectric transducer (PZT) sensor array, is one of the most widely used imaging algorithms to perform active damage monitoring and localization. However, since the sensing paths are distributed inside the sensor array with the non-uniform density, the RAPID algorithm can only localize damage when it is occurring inside of the array. If the damage occurs outside of the array or both inside and outside of the array, that is, multi-type damage, the performance of RAPID algorithm would not be satisfactory. In this paper, a scattering coefficient-based RAPID algorithm with damage indexes separation and imaging fusion is proposed. The amplitude of damage scattered signal at the corresponding time of fight is adopted as the weight in the probability distribution function, and damage indexes are then classified into two categories in the RAPID algorithm for the inside and outside damage localization respectively. Finally, an experiment on the complex composite plate, with the center large hole and surrounding bolt holes, is carried out to verify this proposed method. Experimental results show that this method can realize multi-type damage localization with errors less than 40 mm.","PeriodicalId":51184,"journal":{"name":"Structural Health Monitoring-An International Journal","volume":null,"pages":null},"PeriodicalIF":5.7000,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Health Monitoring-An International Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/14759217231191267","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Guided waves-based structural health monitoring (SHM) methods have potential for practical applications, since they are sensitive to small damages and are able to realize large area monitoring. Among these methods, the Reconstruction Algorithm for Probabilistic Inspection (RAPID), using a Piezoelectric transducer (PZT) sensor array, is one of the most widely used imaging algorithms to perform active damage monitoring and localization. However, since the sensing paths are distributed inside the sensor array with the non-uniform density, the RAPID algorithm can only localize damage when it is occurring inside of the array. If the damage occurs outside of the array or both inside and outside of the array, that is, multi-type damage, the performance of RAPID algorithm would not be satisfactory. In this paper, a scattering coefficient-based RAPID algorithm with damage indexes separation and imaging fusion is proposed. The amplitude of damage scattered signal at the corresponding time of fight is adopted as the weight in the probability distribution function, and damage indexes are then classified into two categories in the RAPID algorithm for the inside and outside damage localization respectively. Finally, an experiment on the complex composite plate, with the center large hole and surrounding bolt holes, is carried out to verify this proposed method. Experimental results show that this method can realize multi-type damage localization with errors less than 40 mm.
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
基于散射系数的RAPID损伤指标分离与图像融合算法在多类型损伤定位中的应用
基于导波的结构健康监测方法对小损伤敏感,能够实现大面积监测,具有实际应用潜力。在这些方法中,使用压电换能器(PZT)传感器阵列的概率检测重建算法(RAPID)是执行主动损伤监测和定位的最广泛使用的成像算法之一。然而,由于传感路径以不均匀的密度分布在传感器阵列内部,RAPID算法只能在阵列内部发生损伤时定位损伤。如果损伤发生在阵列外部或阵列内外,即多类型损伤,RAPID算法的性能将不令人满意。本文提出了一种基于散射系数的RAPID损伤指标分离与图像融合算法。在概率分布函数中,采用相应战斗时间的损伤散射信号幅度作为权重,然后在RAPID算法中将损伤指标分为两类,分别进行内外损伤定位。最后,在具有中心大孔和周边螺栓孔的复合材料板上进行了实验,验证了该方法。实验结果表明,该方法可以实现多类型损伤定位,误差小于40 毫米。
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
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
期刊最新文献
Deep learning-based obstacle-avoiding autonomous UAVs with fiducial marker-based localization for structural health monitoring. Deep learning-based concrete defects classification and detection using semantic segmentation. Combination of active sensing method and data-driven approach for rubber aging detection Distributed fiber optic strain sensing for crack detection with Brillouin shift spectrum back analysis An unsupervised transfer learning approach for rolling bearing fault diagnosis based on dual pseudo-label screening
×
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