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Conference Papers Year : 2023

High Dimensional Data Reduction in Modal Analysis with Stochastic Subspace Identification

Abstract

Subspace system identification methods are widely used in output-only vibration analysis of civil structures, known as operational modal analysis. With the advent of new sensor technologies, such as video camera-based full field displacement or velocity measurements, the number of measured outputs is quickly increasing. In this paper, we propose principal component analysis-based data size reduction methods for efficient application of subspace methods, while preserving the high spatial resolution of the identified mode shapes for detailed modal analysis.
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hal-04214889 , version 1 (22-09-2023)

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Zhilei Luo, Boualem Merainani, Michael Döhler, Vincent Baltazart, Qinghua Zhang. High Dimensional Data Reduction in Modal Analysis with Stochastic Subspace Identification. IFAC 2023 - 22nd International Federation of Automatic Control World Congress, Jul 2023, Yokohama, Japan. pp.1-6, ⟨10.1016/j.ifacol.2023.10.1049⟩. ⟨hal-04214889⟩
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