利用线性判别分析对环境变化和测量噪声下的近海结构进行结构损伤分类

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Structural Control & Health Monitoring Pub Date : 2024-10-21 DOI:10.1155/2024/6650582
Yufeng Jiang, Yu Liu, Shuqing Wang
{"title":"利用线性判别分析对环境变化和测量噪声下的近海结构进行结构损伤分类","authors":"Yufeng Jiang,&nbsp;Yu Liu,&nbsp;Shuqing Wang","doi":"10.1155/2024/6650582","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Changing environmental conditions and measured noises often affect the dynamic responses of structures and can obscure subtle changes in the vibration characteristics caused by damage. To address this issue, a new method for classifying damage in offshore structures under varying environmental conditions and measured noises is proposed using linear discrimination analysis (LDA). Two sets of data on dynamic characteristics, one from healthy structures and the other from unknown testing structures, are used to determine the optimal projection vector. This vector is perpendicular to the discriminant hyperplane and is used for damage classification. The damage-sensitive features are extracted by projecting both sets of data onto this vector. These features are then used with the hypothesis test technique to determine the condition state of the testing structure. Numerical studies on offshore wind turbine structures and experimental validations of a deep-sea mining system are being conducted to evaluate the effectiveness of the proposed approach. The study also examines the impact of mode combinations, measured noises and samples on the performance of the approach. The results indicate that the proposed approach can accurately assess the structural health state even in the presence of environmental changes and noise contamination, even with limited samples. The promising performance of the approach will facilitate the establishment of an online structural monitoring system to ensure the safety of offshore structures.</p>\n </div>","PeriodicalId":49471,"journal":{"name":"Structural Control & Health Monitoring","volume":"2024 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6650582","citationCount":"0","resultStr":"{\"title\":\"Structural Damage Classification in Offshore Structures Under Environmental Variations and Measured Noises Using Linear Discrimination Analysis\",\"authors\":\"Yufeng Jiang,&nbsp;Yu Liu,&nbsp;Shuqing Wang\",\"doi\":\"10.1155/2024/6650582\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p>Changing environmental conditions and measured noises often affect the dynamic responses of structures and can obscure subtle changes in the vibration characteristics caused by damage. To address this issue, a new method for classifying damage in offshore structures under varying environmental conditions and measured noises is proposed using linear discrimination analysis (LDA). Two sets of data on dynamic characteristics, one from healthy structures and the other from unknown testing structures, are used to determine the optimal projection vector. This vector is perpendicular to the discriminant hyperplane and is used for damage classification. The damage-sensitive features are extracted by projecting both sets of data onto this vector. These features are then used with the hypothesis test technique to determine the condition state of the testing structure. Numerical studies on offshore wind turbine structures and experimental validations of a deep-sea mining system are being conducted to evaluate the effectiveness of the proposed approach. The study also examines the impact of mode combinations, measured noises and samples on the performance of the approach. The results indicate that the proposed approach can accurately assess the structural health state even in the presence of environmental changes and noise contamination, even with limited samples. The promising performance of the approach will facilitate the establishment of an online structural monitoring system to ensure the safety of offshore structures.</p>\\n </div>\",\"PeriodicalId\":49471,\"journal\":{\"name\":\"Structural Control & Health Monitoring\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6650582\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Structural Control & Health Monitoring\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/6650582\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Control & Health Monitoring","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/6650582","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

不断变化的环境条件和测量到的噪声经常会影响结构的动态响应,并可能掩盖由损坏引起的振动特性的细微变化。为解决这一问题,我们提出了一种新方法,利用线性判别分析(LDA)对不同环境条件和测量噪声下的海上结构进行损伤分类。使用两组动态特性数据(一组来自健康结构,另一组来自未知测试结构)来确定最佳投影向量。该向量垂直于判别超平面,用于损伤分类。通过将两组数据投影到该向量上,可提取对损伤敏感的特征。然后利用这些特征和假设检验技术来确定测试结构的状态。目前正在对海上风力涡轮机结构进行数值研究,并对深海采矿系统进行实验验证,以评估所提出方法的有效性。研究还考察了模式组合、测量噪声和样本对该方法性能的影响。结果表明,即使存在环境变化和噪声污染,即使样本有限,所提出的方法也能准确评估结构健康状态。该方法的良好性能将有助于建立在线结构监测系统,确保海上结构的安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Structural Damage Classification in Offshore Structures Under Environmental Variations and Measured Noises Using Linear Discrimination Analysis

Changing environmental conditions and measured noises often affect the dynamic responses of structures and can obscure subtle changes in the vibration characteristics caused by damage. To address this issue, a new method for classifying damage in offshore structures under varying environmental conditions and measured noises is proposed using linear discrimination analysis (LDA). Two sets of data on dynamic characteristics, one from healthy structures and the other from unknown testing structures, are used to determine the optimal projection vector. This vector is perpendicular to the discriminant hyperplane and is used for damage classification. The damage-sensitive features are extracted by projecting both sets of data onto this vector. These features are then used with the hypothesis test technique to determine the condition state of the testing structure. Numerical studies on offshore wind turbine structures and experimental validations of a deep-sea mining system are being conducted to evaluate the effectiveness of the proposed approach. The study also examines the impact of mode combinations, measured noises and samples on the performance of the approach. The results indicate that the proposed approach can accurately assess the structural health state even in the presence of environmental changes and noise contamination, even with limited samples. The promising performance of the approach will facilitate the establishment of an online structural monitoring system to ensure the safety of offshore structures.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
期刊最新文献
Damage Identification in Large-Scale Bridge Girders Using Output-Only Modal Flexibility–Based Deflections and Span-Similar Virtual Beam Models A Multiple-Point Deformation Monitoring Model for Ultrahigh Arch Dams Using Temperature Lag and Optimized Gaussian Process Regression A Graph-Based Methodology for Optimal Design of Inerter-Based Passive Vibration Absorbers With Minimum Complexity Automatic Identification and Segmentation of Long-Span Rail-and-Road Cable-Stayed Bridges Using UAV LiDAR Point Cloud Development of 6 Degrees of Freedom Parallel-Link Shaking Table for Three-Dimensional Movement on Centrifugal Loading Device
×
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