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Uncertainty bound quantification for structural modal parameters via the random decrement technique

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Uncertainty inevitably exists in operational modal analysis of civil structures, harming the reliability of estimated structural dynamic properties. Despite being one of the most widely adopted modal identification methods, the random decrement technique (RDT) still lacks an uncertainty quantification means to determine the uncertainty bounds for its modal identification results. Therefore, this paper proposes an uncertainty bound quantification method for structural modal parameters identified via the RDT to fill the research gap, which can be used to evaluate the reliability of modal identification results from the RDT. Specifically, the covariance matrix calculated from the random decrement segments is treated as the source of uncertainty, based on which the uncertainty bounds of identified modal parameters can be obtained via the first-order perturbation analysis. Through a set of single-degree-of-freedom numerical simulation models, the effectiveness of the proposed method is comprehensively investigated, and an uncertainty-based reliability evaluation indicator is developed. Furthermore, the applicability of the proposed method is demonstrated using vibration signals recorded from a 600-m-tall skyscraper. This paper aims to propose a novel uncertainty quantification method for modal parameters via the RDT and enhance the comprehension of uncertainty quantification concerning the modal parameters of civil structures. © 2025 Elsevier Ltd.
Original languageEnglish
Article number112821
JournalJournal of Building Engineering
Volume108
Online published1 May 2025
DOIs
Publication statusPublished - 15 Aug 2025

Funding

The work described in this paper was fully supported by grants from the Research Grants Council of Hong Kong (TRS: T22-501/23-R; CRF: C5004-23 GF; RIF: R1006-23).

Research Keywords

  • Civil structures
  • Modal identification
  • Random decrement technique
  • Uncertainty quantification

RGC Funding Information

  • RGC-funded

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