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Published March 1, 2023 | public
Journal Article

Automated modal identification by quantification of high-spatial-resolution response measurements

Abstract

Identifying modal parameters from vibration measurements is an essential step for modal analysis and modeling of structural dynamics. A critical challenge in modal parameter identification is the determination of the physical modes from spurious modes, especially with noisy measurement data. In this study, an approach is presented to enable automated identification of modal parameters by quantifying the spatial features of full-field, high-spatial-resolution response measurements. Specifically, it is derived that the local variances of the physical and spurious mode shapes are drastically distinguishing, especially when the spatial resolution of the response measurement is high (i.e., full-field with dense spatial measurement points). This allows an effective identification of the physical modes from spurious. Experimental studies are conducted on a few structural models and detailed comparisons are performed and discussed between the presented method and existing methods, including parametric and non-parametric.

Additional Information

© 2022 Elsevier. This research was partially funded by the Physics of Artificial Intelligence Program of U.S. Defense Advanced Research Projects Agency (DARPA) and Michigan Tech faculty startup fund. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional details

Created:
August 22, 2023
Modified:
October 25, 2023