Three-dimensional off-grid localization of incipient tip vortex cavitation using Bayesian inference

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Abstract

In this paper, we propose a 3-D source localization method to determine the incipient tip vortex cavitation (TVC) positions by constructing a signal model for the broadband off-grid cavitation. Subsequently, the conventional sparse Bayesian learning (SBL), whose performance is diminished owing to an inappropriate signal representation for the off-grid TVC by basis mismatch, was extended to solve the signal model via Taylor series and the block-sparse based broadband off-grid approach (off-grid BSBL). The off-grid BSBL was examined using synthetic and experimental cavitation tunnel data. Furthermore, its localization results were compared with those for conventional and adaptive beamformers and on-grid BSBL, which generally suffer from low resolutions and basis mismatch, respectively. When the off-grid BSBL was applied to chirp- and pop-type signals from incipient TVC, it determined the TVC positions near the top center of the propeller and provided the clearest localization results among the schemes considered.

Original languageEnglish
Article number112124
JournalOcean Engineering
Volume261
DOIs
StatePublished - 1 Oct 2022

Keywords

  • 3-D off-grid source localization
  • Incipient tip vortex cavitation
  • Sparse Bayesian learning

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