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Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques.

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Title: Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques.
Authors: Jang, Hye-Sook1 (AUTHOR), An, Jae-Hyoung1 (AUTHOR), Eun, Hee-Chang1 (AUTHOR)
Source: International Journal of Distributed Sensor Networks. 2/26/2024, Vol. 2024, p1-12. 12p.
Subjects: Substructuring techniques, Parameter estimation, System identification, Resonance
Abstract: This study presents frequency-based substructuring (FBS) techniques and an identification method for predicting joint parameters. Two FBS techniques, FBS-1 and FBS-2, were derived by assuming pseudomasses at the joint nodes between adjacent substructures. It is estimated that the main reason for the discrepancy with the analytical FRFs is the difficulty in describing the low-frequency responses owing to the assumed pseudomasses of the substructures. Although the FRF curve based on the FBS-2 technique is very close to the analytical FRF curve up to the first resonance frequency, some inconsistencies occur thereafter. It is analyzed that the FRFs up to the first resonance frequency can be utilized for data expansion methods and system identification techniques. Paying attention to this result, this study also provides an identification method to estimate the joint parameters based on the FRF variation. Its validity is illustrated using a numerical example. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Distributed Sensor Networks is the property of Wiley-Blackwell 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.)
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DbLabel: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques.
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  Data: <searchLink fieldCode="AR" term="%22Jang%2C+Hye-Sook%22">Jang, Hye-Sook</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22An%2C+Jae-Hyoung%22">An, Jae-Hyoung</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Eun%2C+Hee-Chang%22">Eun, Hee-Chang</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Distributed+Sensor+Networks%22">International Journal of Distributed Sensor Networks</searchLink>. 2/26/2024, Vol. 2024, p1-12. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Substructuring+techniques%22">Substructuring techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22System+identification%22">System identification</searchLink><br /><searchLink fieldCode="DE" term="%22Resonance%22">Resonance</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study presents frequency-based substructuring (FBS) techniques and an identification method for predicting joint parameters. Two FBS techniques, FBS-1 and FBS-2, were derived by assuming pseudomasses at the joint nodes between adjacent substructures. It is estimated that the main reason for the discrepancy with the analytical FRFs is the difficulty in describing the low-frequency responses owing to the assumed pseudomasses of the substructures. Although the FRF curve based on the FBS-2 technique is very close to the analytical FRF curve up to the first resonance frequency, some inconsistencies occur thereafter. It is analyzed that the FRFs up to the first resonance frequency can be utilized for data expansion methods and system identification techniques. Paying attention to this result, this study also provides an identification method to estimate the joint parameters based on the FRF variation. Its validity is illustrated using a numerical example. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Distributed Sensor Networks is the property of Wiley-Blackwell 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.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1155/2024/6684449
    Languages:
      – Code: eng
        Text: English
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        PageCount: 12
        StartPage: 1
    Subjects:
      – SubjectFull: Substructuring techniques
        Type: general
      – SubjectFull: Parameter estimation
        Type: general
      – SubjectFull: System identification
        Type: general
      – SubjectFull: Resonance
        Type: general
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      – TitleFull: Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques.
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            NameFull: Jang, Hye-Sook
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            NameFull: An, Jae-Hyoung
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            NameFull: Eun, Hee-Chang
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            – D: 26
              M: 02
              Text: 2/26/2024
              Type: published
              Y: 2024
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              Value: 2024
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            – TitleFull: International Journal of Distributed Sensor Networks
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