Impact force identification for composite structures using adaptive wavelet-regularised deconvolution
File(s)
Published version
Author(s)
Xiao, Dong
Sharif-Khodaei, Zahra
Aliabadi, MH
Type
Journal Article
Abstract
Impact force identification (IFI) through deconvolution methods from measured structural responses poses a challenge due to the ill-posed nature of the inversion problem. Regularisation techniques, such as Tikhonov, sparse, and wavelet regularisation, offer potential solutions to mitigate the ill-posedness. However, determining suitable regularisation parameters is time-consuming. This study presents an adaptive wavelet-regularised time-domain deconvolution method for efficient IFI, based on wavelet transform and multi-resolution analysis. By analysing impact sensor signals using wavelets, adaptive impact windows covering the entire impact duration are generated, reducing signal length for deconvolution. Multi-resolution analysis of sensor signals enables identification of wavelet bases for the multi-resolution representation of impact force history. Regularisation is achieved by filtering out insignificant wavelet bases based on their energy contributions. Validation is performed through experiments involving small-mass hammer and large-mass drop tower impacts, comparing against various deconvolution methods. Results demonstrate the superior computational efficiency and comparable accuracy of the proposed adaptive method in IFI across different time windows. Notably, accurate force deconvolution for large-mass impacts confirms the effectiveness of the deconvolution methods for IFI, particularly when the structure undergoes significant local deformation.
Date Issued
2024-11-01
Date Acceptance
2024-06-04
Citation
Mechanical Systems and Signal Processing, 2024, 220
ISSN
0888-3270
Publisher
Elsevier BV
Journal / Book Title
Mechanical Systems and Signal Processing
Volume
220
Copyright Statement
© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
(http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.1016/j.ymssp.2024.111608
Publication Status
Published
Article Number
111608
Date Publish Online
2024-06-17