• Square-shaped sensor clusters for acoustic source localization in anisotropic plates by wave front shape-based approach

      Sen, Novonil; Gawroński, Mateusz; Packo, Pawel; Uhl, Tadeusz; Kundu, Tribikram; Department of Aerospace and Mechanical Engineering, University of Arizona; Department of Civil and Architectural Engineering and Mechanics, University of Arizona (Elsevier BV, 2021-05)
      Various techniques have emerged in the past few years for localizing the acoustic source in an anisotropic plate. The wave front shape-based approach, one of the recent additions to this field of research, has the advantage of circumventing the unrealistic assumption of a straight line wave propagation path through an anisotropic medium. In their most recent versions, the two major wave front shape-based techniques (i.e., the ellipse- and the parametric curve-based techniques) are applicable to the situations with an unknown orientation of the axes of symmetry of an anisotropic plate. However, this approach still relies on estimating the angle of wave-incidence at a given location of the plate via a single L-shaped sensor cluster. The incidence angle so obtained may deviate significantly from the true angle of wave arrival. To improve the estimation accuracy of the incidence angle, in the present study a square-shaped cluster composed of four densely-spaced sensors forming the four vertices of a square is proposed to be installed at the location of interest. Essentially, a square-shaped sensor cluster contains four L-shaped clusters oriented in different directions. A formulation to estimate the angle of incidence from the signal data acquired by a squared-shaped cluster is presented. The wave front shape-based approach can then be applied to estimate the acoustic source location. A numerical study is conducted to illustrate the proposed methodology. Performance comparisons between square- and L-shaped clusters reveal that in general the square-shaped clusters lead to more accurate source location estimates than the L-shaped clusters. © 2020 Elsevier Ltd