Experimental Modal Analysis of Angle Signals Based on the Stochastic Subspace Identification Method

In-Ho Kim
{"title":"Experimental Modal Analysis of Angle Signals Based on the Stochastic Subspace Identification Method","authors":"In-Ho Kim","doi":"10.24949/njes.v14i2.672","DOIUrl":null,"url":null,"abstract":"This paper aims to verify the extraction of modal parameters from angle signals using the stochastic subspace identification (SSI) method. The use of angle signal-based mode shapes can reduce the loss of node information and enhance the robustness in curva-ture-based damage detection. In this regard, the system identification of angle signals should be first conducted prior to the damage detection. For large structures, an out-put-only system identification method should be considered for the modal analysis of an-gle signals, because artificial shaking excitation or impact excitation is practically impos-sible. In order to achieve this, the SSI method is used; it is one of the most powerful tools among the output-only system identification methods because it does not cover nonlinear problems. In order to demonstrate the system identification process of angle signals using the SSI method, the transformation matrix is assumed to represent the relationship be-tween the angular displacement and the normal displacement. Next, the modified block Hankel matrix that consists of angle signals, which can be expressed as a multiplication between the transformation matrix and displacement series vector, is constructed. The observability matrix can be estimated using the singular value decomposition for the pro-jection of the future part onto the past part of the modified block Hankel matrix. Finally, the natural frequencies and angle signal-based mode shapes are calculated using the state and observation matrices. In order to verify the results of the analytical studies, the modal properties estimated from the numerical simulation and the SSI method using angu-lar-velocity measurements are compared.","PeriodicalId":338631,"journal":{"name":"NUST Journal of Engineering Sciences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NUST Journal of Engineering Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24949/njes.v14i2.672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper aims to verify the extraction of modal parameters from angle signals using the stochastic subspace identification (SSI) method. The use of angle signal-based mode shapes can reduce the loss of node information and enhance the robustness in curva-ture-based damage detection. In this regard, the system identification of angle signals should be first conducted prior to the damage detection. For large structures, an out-put-only system identification method should be considered for the modal analysis of an-gle signals, because artificial shaking excitation or impact excitation is practically impos-sible. In order to achieve this, the SSI method is used; it is one of the most powerful tools among the output-only system identification methods because it does not cover nonlinear problems. In order to demonstrate the system identification process of angle signals using the SSI method, the transformation matrix is assumed to represent the relationship be-tween the angular displacement and the normal displacement. Next, the modified block Hankel matrix that consists of angle signals, which can be expressed as a multiplication between the transformation matrix and displacement series vector, is constructed. The observability matrix can be estimated using the singular value decomposition for the pro-jection of the future part onto the past part of the modified block Hankel matrix. Finally, the natural frequencies and angle signal-based mode shapes are calculated using the state and observation matrices. In order to verify the results of the analytical studies, the modal properties estimated from the numerical simulation and the SSI method using angu-lar-velocity measurements are compared.
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
基于随机子空间辨识方法的角度信号实验模态分析
本文旨在验证利用随机子空间识别(SSI)方法从角度信号中提取模态参数的有效性。利用基于角度信号的模态振型可以减少节点信息的丢失,增强基于曲率的损伤检测的鲁棒性。因此,在进行损伤检测之前,首先要对角度信号进行系统识别。对于大型结构,由于人工的振动激励或冲击激励在实际中是不可能的,因此对角信号进行模态分析时应考虑一种仅输出的系统识别方法。为了实现这一点,使用了SSI方法;由于它不涉及非线性问题,因此是纯输出系统识别方法中最强大的工具之一。为了演示SSI方法对角度信号的系统识别过程,假设用变换矩阵表示角位移与法向位移之间的关系。其次,构造由角度信号组成的修正块汉克尔矩阵,该矩阵可表示为变换矩阵与位移级数向量的乘积。利用改进的块汉克尔矩阵的未来部分到过去部分的投影的奇异值分解来估计可观测矩阵。最后,利用状态矩阵和观测矩阵计算了基于固有频率和角度信号的模态振型。为了验证解析研究的结果,将数值模拟估计的模态特性与采用角速度测量的SSI方法进行了比较。
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
Structural Analysis & Shape Optimization for a Control Arm of a Vehicle’s Suspension. Investigating Ground subsidence due to Secret Mining and Repairing Damaged Structures Catalytic Reduction of Carbon dioxide to Methanol as a Fuel, A Mini Review Structural Properties of Mn Doped ZnO Nanocrystallites Using Wet Chemical Synthesis Structural Optimization of Metallic Toroid using Finite Element Method
×
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