Broadband sound absorption has long been a concern in noise control engineering, but the inverse design of multi-parallel microperforated panels (MPPs) for broadband sound absorption remains challenging. To address this issue, we propose a deep learning model that combines a variational autoencoder (VAE) with a physics-informed neural network (PINN) to accelerate the inverse design process of a multi-parallel MPP. Following Maa’s theory, we generated a dataset of 500,000 samples to train the model. By incorporating the PINN, we added an acoustic physical constraint to the loss function, promoting model convergence and the derivation of stable, unified parameters. The efficacy of the inverse design model was validated through theoretical analysis, finite element simulations, and impedance tube experiments. The experimental results show that the average sound absorption coefficient of multi-parallel MPPs within the frequency range of 500–1200 Hz is 0.85. Our work contributes to accelerating the inverse design of multi-parallel acoustic metamaterials.

In the process of using laser interference calibration method to calibrate high-frequency hydrophones, a transparent reflective film will be used. This article studies the influence of the film on the calibration results. The theoretical calculation formula for the sound pressure transmission coefficient of thin films was derived through the impedance transfer method of multi-layer media. It can be observed that the sound pressure transmission coefficient decreases with increasing frequency, which means that the higher the frequency, the greater the influence of the thin film. When the ultrasonic frequency reaches 10 MHz, the sound pressure transmission coefficient of the thin film with a thickness of 15 μm decreases to 0.9017. The sound pressure measured by the laser Doppler vibrometer method was corrected by the sound pressure transmission coefficient and compared with the results measured by a standard hydrophone. Experiments were conducted to measure the sound pressure at frequencies of 1, 2, 3, 5, and 10 MHz. The results showed that correcting the measurement results of the laser vibrometer method by the sound pressure transmission coefficient can effectively reduce measurement errors.