| Autor: |
Yanan Wang, Lin Chen, Junjiang Liu, Baijie Qiao, Weifeng He, Xuefeng Chen |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Chinese Journal of Mechanical Engineering, Vol 37, Iss 1, Pp 1-19 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2192-8258 |
| DOI: |
10.1186/s10033-024-01044-2 |
| Popis: |
Abstract In practice, simultaneous impact localization and time history reconstruction can hardly be achieved, due to the ill-posed and under-determined problems induced by the constrained and harsh measuring conditions. Although $$\ell_{1}$$ ℓ 1 regularization can be used to obtain sparse solutions, it tends to underestimate solution amplitudes as a biased estimator. To address this issue, a novel impact force identification method with $$\ell_{p}$$ ℓ p regularization is proposed in this paper, using the alternating direction method of multipliers (ADMM). By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators, ADMM can address the challenge effectively. To mitigate the sensitivity to regularization parameters, an adaptive regularization parameter is derived based on the K-sparsity strategy. Then, an ADMM-based sparse regularization method is developed, which is capable of handling $$\ell_{p}$$ ℓ p regularization with arbitrary p values using adaptively-updated parameters. The effectiveness and performance of the proposed method are validated on an aircraft skin-like composite structure. Additionally, an investigation into the optimal p value for achieving high-accuracy solutions via $$\ell_{p}$$ ℓ p regularization is conducted. It turns out that $$\ell_{0.6}$$ ℓ 0.6 regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classic $$\ell_{1}$$ ℓ 1 regularization method. The impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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