Bayesian operational modal analysis with asynchronous data, part I: Most probable value

Zhu, Yi-Chen and Au, Siu-Kui ORCID: 0000-0002-0228-1796 (2018) Bayesian operational modal analysis with asynchronous data, part I: Most probable value. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 98. pp. 652-666.

Text Bayesian Operational Modal Analysis with Asynchronous Data Part I Most Probable Value.pdf - Author Accepted Manuscript Download (723kB)

Abstract

In vibration tests, multiple sensors are used to obtain detailed mode shape information about the tested structure. Time synchronisation among data channels is required in conventional modal identification approaches. Modal identification can be more flexibly conducted if this is not required. Motivated by the potential gain in feasibility and economy, this work proposes a Bayesian frequency domain method for modal identification using asynchronous ‘output-only’ ambient data, i.e. ‘operational modal analysis’. It provides a rigorous means for identifying the global mode shape taking into account the quality of the measured data and their asynchronous nature. This paper (Part I) proposes an efficient algorithm for determining the most probable values of modal properties. The method is validated using synthetic and laboratory data. The companion paper (Part II) investigates identification uncertainty and challenges in applications to field vibration data.

Item Type:	Article
Uncontrolled Keywords:	Ambient data, Asynchronous data, Bayesian methods, FFT, Operational modal analysis
Depositing User:	Symplectic Admin
Date Deposited:	31 May 2017 07:24
Last Modified:	19 Jan 2023 07:03
DOI:	10.1016/j.ymssp.2017.05.027
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3007716