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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Smart Structures and Systems, An International Journal Smart Structures and Systems, An International Journal Vol.25 No.3
- 발행연도
- 2020.1
- 수록면
- 369 - 384 (16page)
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초록· 키워드
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A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l1-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.
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참고문헌 (41)
참고문헌 신청
Alguri, K. S. / 2016 / Consolidating guided wave simulations and experimental data : a dictionary learning approach / Proceedings of SPIE Smart Structures and Materials, Nondestructive Evaluation and Health Monitoring
Amir Beck / 2009 / A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems / SIAM Journal on Imaging Sciences 2(1):183~202
J.M. Bioucas-Dias / 2007 / A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration / IEEE Transactions on Image Processing 16(12):2992~3004
Candes, E. / 2007 / Sparsity and incoherence in compressive sampling / Inverse Probl 23(3):969
E.J. Candes / 2008 / An Introduction To Compressive Sampling / IEEE Signal Processing Magazine 25(2):21~30
Amir Beck / 2009 / A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems / SIAM Journal on Imaging Sciences 2(1):183~202
J.M. Bioucas-Dias / 2007 / A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration / IEEE Transactions on Image Processing 16(12):2992~3004
Candes, E. / 2007 / Sparsity and incoherence in compressive sampling / Inverse Probl 23(3):969
E.J. Candes / 2008 / An Introduction To Compressive Sampling / IEEE Signal Processing Magazine 25(2):21~30
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