2021
DOI: 10.3390/app112110152
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Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity

Abstract: Damage identification methods based on structural modal parameters are influenced by the structure form, number of measuring sensors and noise, resulting in insufficient modal data and low damage identification accuracy. The additional virtual mass method introduced in this study is based on the virtual deformation method for deriving the frequency-domain response equation of the virtual structure and identify its mode to expand the modal information of the original structure. Based on the initial condition as… Show more

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Cited by 3 publications
(2 citation statements)
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“…The iteration stopping criterion is the estimated damage vector sparsity or the termination threshold set in advance, which is empirical in nature. To address this problem, Zhang et al [36] proposed an improved OMP (IOMP) algorithm to obtain more stable and accurate sparse damage identification results. The objective function used for damage identification derived in Ref [36] is shown in Equation (9).…”
Section: Optimization Based On Improved Orthogonal Matching Pursuit (...mentioning
confidence: 99%
See 1 more Smart Citation
“…The iteration stopping criterion is the estimated damage vector sparsity or the termination threshold set in advance, which is empirical in nature. To address this problem, Zhang et al [36] proposed an improved OMP (IOMP) algorithm to obtain more stable and accurate sparse damage identification results. The objective function used for damage identification derived in Ref [36] is shown in Equation (9).…”
Section: Optimization Based On Improved Orthogonal Matching Pursuit (...mentioning
confidence: 99%
“…To address this problem, Zhang et al [36] proposed an improved OMP (IOMP) algorithm to obtain more stable and accurate sparse damage identification results. The objective function used for damage identification derived in Ref [36] is shown in Equation (9).…”
Section: Optimization Based On Improved Orthogonal Matching Pursuit (...mentioning
confidence: 99%