International Journal of Distributed Sensor Networks (Jan 2024)

Estimation of Joint Parameters Using Frequency-Based Substructuring Techniques

  • Hye-Sook Jang,
  • Jae-Hyoung An,
  • Hee-Chang Eun

DOI
https://doi.org/10.1155/2024/6684449
Journal volume & issue
Vol. 2024

Abstract

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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.