Imaging damage in plate waveguides using frequency-domain multiple signal classification (F-MUSIC)

Xiongbin Yang, Kai Wang, Pengyu Zhou, Lei Xu, Zhongqing Su

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)


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.

Original languageEnglish
Article number106607
Publication statusPublished - Feb 2022


  • Frequency domain analysis
  • Guided ultrasonic waves
  • Multiple signal classification (MUSIC)
  • Sparse sensor network
  • Ultrasonic imaging

ASJC Scopus subject areas

  • Acoustics and Ultrasonics


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