TY - JOUR
T1 - Imaging damage in plate waveguides using frequency-domain multiple signal classification (F-MUSIC)
AU - Yang, Xiongbin
AU - Wang, Kai
AU - Zhou, Pengyu
AU - Xu, Lei
AU - Su, Zhongqing
N1 - Funding Information:
The work was supported by a General Project (No. 51875492) and a Key Project (No. 51635008) received from the National Natural Science Foundation of China. Z Su acknowledges the support from the Hong Kong Research Grants Council via General Research Funds (Nos. 15202820, 15204419 and 15212417).
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/2
Y1 - 2022/2
N2 - Earlier, an ameliorated MUSIC (Am-MUSIC) algorithm is developed by the authors [1], aimed at expanding conventional MUSIC algorithm from linear array-facilitated nondestructive evaluation to in situ health monitoring with a sparse sensor network. Yet, Am-MUSIC leaves a twofold issue to be improved: i) the signal representation equation is constructed at each pixel across the inspection region, incurring high computational cost; and ii) the algorithm is applicable to monochromatic excitation only, ignoring signal features scattered out of the excitation frequency band which also carry information on structural integrity. With this motivation, a multiple-damage-scattered wavefield model is developed, with which the signal representation equation is constructed in the frequency domain, avoiding computationally expensive pixel-based calculation – referred to as frequency-domain MUSIC (F-MUSIC). F-MUSIC quantifies the orthogonal attributes between the signal subspace and noise subspace inherent in signal representation equation, and generates a full spatial spectrum of the inspected sample to visualize damage. Modeling in the frequency domain endows F-MUSIC with the capacity to fuse rich information scattered in a broad band and therefore enhance imaging precision. Both simulation and experiment are performed to validate F-MUSIC when used for imaging single and multiple sites of damage in an isotropic plate waveguide with a sparse sensor network. Results accentuate that effectiveness of F-MUSIC is not limited by the quantity of damage, and imaging precision is not downgraded due to the use of a highly sparse sensor network – a challenging task for conventional MUSIC algorithm to fulfil.
AB - Earlier, an ameliorated MUSIC (Am-MUSIC) algorithm is developed by the authors [1], aimed at expanding conventional MUSIC algorithm from linear array-facilitated nondestructive evaluation to in situ health monitoring with a sparse sensor network. Yet, Am-MUSIC leaves a twofold issue to be improved: i) the signal representation equation is constructed at each pixel across the inspection region, incurring high computational cost; and ii) the algorithm is applicable to monochromatic excitation only, ignoring signal features scattered out of the excitation frequency band which also carry information on structural integrity. With this motivation, a multiple-damage-scattered wavefield model is developed, with which the signal representation equation is constructed in the frequency domain, avoiding computationally expensive pixel-based calculation – referred to as frequency-domain MUSIC (F-MUSIC). F-MUSIC quantifies the orthogonal attributes between the signal subspace and noise subspace inherent in signal representation equation, and generates a full spatial spectrum of the inspected sample to visualize damage. Modeling in the frequency domain endows F-MUSIC with the capacity to fuse rich information scattered in a broad band and therefore enhance imaging precision. Both simulation and experiment are performed to validate F-MUSIC when used for imaging single and multiple sites of damage in an isotropic plate waveguide with a sparse sensor network. Results accentuate that effectiveness of F-MUSIC is not limited by the quantity of damage, and imaging precision is not downgraded due to the use of a highly sparse sensor network – a challenging task for conventional MUSIC algorithm to fulfil.
KW - Frequency domain analysis
KW - Guided ultrasonic waves
KW - Multiple signal classification (MUSIC)
KW - Sparse sensor network
KW - Ultrasonic imaging
UR - http://www.scopus.com/inward/record.url?scp=85116857224&partnerID=8YFLogxK
U2 - 10.1016/j.ultras.2021.106607
DO - 10.1016/j.ultras.2021.106607
M3 - Journal article
AN - SCOPUS:85116857224
SN - 0041-624X
VL - 119
JO - Ultrasonics
JF - Ultrasonics
M1 - 106607
ER -