Optimization of sonar transducers via evolutionary algorithms

Abstract

Tonpilz acoustic transducer is a device for detecting objects under the water and measuring their properties. The Tonpilz includes a stack of piezoelectric actuators polarized across their thickness. The range of pressure level on the working frequency band and the sound pressure level at the resonance frequency are two crucial factors determining the performance of the transducer. A large number of structural and material attributes makes the design process of Tonpilz difficult. This study aims to improve the performance of a Tonpilz by using the optimization to find the globally optimum design variable set. A multi-objective function is introduced based on transducer performance measures. Furthermore, the problem of mixed-integer programming is addressed. Based on the geometrical and operational limits, a series of constraints were introduced in the optimization problem. The results show that optimizing the design variables greatly enhances performance.

A new algorithm to calculate complex material parameters in piezoelectric stacks

“…To overcome this problem, non-gradient-based methods, evolutionary algorithms (EAs), could be solutions since they do not require sensitivity information of the functions because of using random searching techniques in given design spaces. Some noticeable EAs for the estimation of piezoelectricity materials are included genetic algorithms (F. Karami and R. Morsali (2019)), differential evolution (C. S. Feng et al(2021), T. Liu et al (2017), G. Wang et al (2015)), and so on.…”