Sound field visualization around a rigid object based on physics-informed neural networks

Sound field visualization helps us understand the complicated sound propagation. However, it is difficult to visualize the sound field in detail because it requires many measurement points. In this study, based on physical models and deep learning, we propose the visualization method of a scattered sound field around a rigid object, including non-spherical geometry, with a small number of microphones. From the simulation experiments in the two-dimensional sound fields, the proposed method improved the estimation accuracy by introducing the boundary conditions in addition to the wave equation.