View in EDS

Response Prediction of Lumped Mass Structures Based on Physical Parameter Identification through Experimental Modal Analysis.

Saved in:
Bibliographic Details
Title: Response Prediction of Lumped Mass Structures Based on Physical Parameter Identification through Experimental Modal Analysis.
Authors: Qu, Chun-Xu1 (AUTHOR) quchunxu@dlut.edu.cn, Liu, Chang-Chong2 (AUTHOR) liuchch@mail.dlut.edu.cn, Yi, Ting-Hua3 (AUTHOR) yth@bucea.edu.cn, Li, Hong-Nan1 (AUTHOR) hnli@dlut.edu.cn
Source: Journal of Engineering Mechanics. May2026, Vol. 152 Issue 5, p1-15. 15p.
Subjects: Modal analysis, Lumped parameter systems, Active noise & vibration control, Structural dynamics, Parameter estimation, Reduced-order models
Abstract: Response prediction, which is an important part of structural dynamic analysis, plays a significant role in dynamic optimization and vibration control of structures. It ensures that the plan of structural reinforcement and vibration control are effective and cost-effective. The traditional method for validation, which is based on the finite-element model, is complex, time-consuming, and susceptible to modeling errors. To address these limitations, in this study, a structural response prediction method based on experimental modal analysis is proposed. First, dynamic testing of the structure is performed. Experimental modal analysis is used to identify modal parameters and reduce noise interference in the measured data. Using the measured data as the starting point of the analysis eliminates the influence of modeling errors. Then, the surrogate model is established based on the modal parameters, and the relationship between the real structure and the surrogate model is given. Structural modification and response prediction are carried out based on the surrogate model, accounting for both modification of local physical parameters and the addition of component. Finally, a numerical example, a benchmark model application, and a test of a lumped mass structure are employed to validate the effectiveness of the proposed method. The results demonstrate that the method accurately predicts structural responses even in the presence of modal truncation. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Engineering Mechanics is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 192320946
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Response Prediction of Lumped Mass Structures Based on Physical Parameter Identification through Experimental Modal Analysis.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Qu%2C+Chun-Xu%22">Qu, Chun-Xu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> quchunxu@dlut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Chang-Chong%22">Liu, Chang-Chong</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> liuchch@mail.dlut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yi%2C+Ting-Hua%22">Yi, Ting-Hua</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> yth@bucea.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Hong-Nan%22">Li, Hong-Nan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hnli@dlut.edu.cn</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Engineering+Mechanics%22">Journal of Engineering Mechanics</searchLink>. May2026, Vol. 152 Issue 5, p1-15. 15p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Modal+analysis%22">Modal analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Lumped+parameter+systems%22">Lumped parameter systems</searchLink><br /><searchLink fieldCode="DE" term="%22Active+noise+%26+vibration+control%22">Active noise & vibration control</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+dynamics%22">Structural dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Reduced-order+models%22">Reduced-order models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Response prediction, which is an important part of structural dynamic analysis, plays a significant role in dynamic optimization and vibration control of structures. It ensures that the plan of structural reinforcement and vibration control are effective and cost-effective. The traditional method for validation, which is based on the finite-element model, is complex, time-consuming, and susceptible to modeling errors. To address these limitations, in this study, a structural response prediction method based on experimental modal analysis is proposed. First, dynamic testing of the structure is performed. Experimental modal analysis is used to identify modal parameters and reduce noise interference in the measured data. Using the measured data as the starting point of the analysis eliminates the influence of modeling errors. Then, the surrogate model is established based on the modal parameters, and the relationship between the real structure and the surrogate model is given. Structural modification and response prediction are carried out based on the surrogate model, accounting for both modification of local physical parameters and the addition of component. Finally, a numerical example, a benchmark model application, and a test of a lumped mass structure are employed to validate the effectiveness of the proposed method. The results demonstrate that the method accurately predicts structural responses even in the presence of modal truncation. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Engineering Mechanics is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=192320946
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1061/JENMDT.EMENG-8304
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 1
    Subjects:
      – SubjectFull: Modal analysis
        Type: general
      – SubjectFull: Lumped parameter systems
        Type: general
      – SubjectFull: Active noise & vibration control
        Type: general
      – SubjectFull: Structural dynamics
        Type: general
      – SubjectFull: Parameter estimation
        Type: general
      – SubjectFull: Reduced-order models
        Type: general
    Titles:
      – TitleFull: Response Prediction of Lumped Mass Structures Based on Physical Parameter Identification through Experimental Modal Analysis.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Qu, Chun-Xu
      – PersonEntity:
          Name:
            NameFull: Liu, Chang-Chong
      – PersonEntity:
          Name:
            NameFull: Yi, Ting-Hua
      – PersonEntity:
          Name:
            NameFull: Li, Hong-Nan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 07339399
          Numbering:
            – Type: volume
              Value: 152
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Journal of Engineering Mechanics
              Type: main
ResultId 1