Apiezoelectric ultrasonic transducer (PUT) is widely used in nondestructive testing, medical imaging, and particle manipulation, etc., and the performance of the PUT determines its functional performance and effectiveness in these applications. The optimization design method of a PUT is very important for the fabrication of a high-performance PUT. In this paper, traditional and efficient optimization design methods for a PUT are presented. The traditional optimization design methods are mainly based on an analytical model, an equivalent circuit model, or a finite element model and the design parameters are adjusted by a trial-and-error method, which relies on the experience of experts and has a relatively low efficiency. Recently, by combining intelligent optimization algorithms, efficient optimization design methods for a PUT have been developed based on a traditional model or a data-driven model, which can effectively improve the design efficiency of a PUT and reduce its development cycle and cost. The advantages and disadvantages of the presented methods are compared and discussed. Finally, the optimization design methods for PUT are concluded, and their future perspectives are discussed.
Keywords: data-driven model; finite element model; intelligent optimization algorithm; optimization design; piezoelectric ultrasonic transducer.