Compressed sensing for OMA using full-field vibration images



Chang, Yen-Hao, Wang, Weizhuo, Chang, Jen-Yuan and Mottershead, John E ORCID: 0000-0003-1279-2562
(2019) Compressed sensing for OMA using full-field vibration images. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 129. pp. 394-406.

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Abstract

Optically-acquired data, typically from digital image correlation, is increasingly being used in the area of structural dynamics, particularly modal testing and damage identification. One of the problems with such data is its extremely large size. Single images regularly extend to tens or even hundreds of thousands of data points and many thousands of images may be required for a vibration test. Such data must be stored and transmitted efficiently for later remote reconstruction and analysis, typically operational modal analysis. It is this requirement that is addressed in the research presented in this paper. This research builds upon previous work whereby digitised optical data was projected onto an orthogonal basis with coefficients (shape descriptors)of either greater or lesser significance; those deemed to be insignificant, according to a chosen threshold being removed. Data reduction by a combination of shape-descriptor decomposition and compressed-sensing is applied to an industrial printed circuit board and reconstructed for operational modal analysis by ℓ1 optimisation.

Item Type: Article
Uncontrolled Keywords: Compressed sensing, Shape descriptor, Sparse representation, Structural health monitoring, Operational modal analysis
Depositing User: Symplectic Admin
Date Deposited: 07 May 2019 07:36
Last Modified: 19 Jan 2023 00:51
DOI: 10.1016/j.ymssp.2019.04.031
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3039757