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arXiv · 2603.14205

Data-driven Experimental Modal Analysis by Dynamic Mode Decomposition

Akira Saito·Tomohiro Kuno
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Abstract

This paper discusses the application of Dynamic Mode Decomposition (DMD) to the extraction of modal properties of linear mechanical systems, i.e., experimental modal analysis (EMA). First, theoretical background of the DMD is briefly reviewed and its relevance to the Ibrahim time-domain method is discussed. Second, DMD is applied to a single DOF system and multi-DOF discrete system to discuss the applicability and interpretation of the DMD as a method of EMA. Furthermore, the effects of measurement errors on the results of DMD are discussed. It is shown that with relatively small measurement errors, DMD can capture modal parameters accurately. However, with relatively large measurement errors, DMD fails to capture modal parameters. Finally, DMD is applied to experimentally-obtained displacement field of a cantilevered beam, and its modal parameters are extracted. It is shown that the modal parameters extracted by DMD are as accurate as the ones obtained by the existing modal parameter extraction method.

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BibTeXRIS

Akira Saito, Tomohiro Kuno. 2026-03-15. Data-driven Experimental Modal Analysis by Dynamic Mode Decomposition. https://doi.org/10.1016/j.jsv.2020.115434

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