An Efficient Optimization Design of Liquid Lens for Acoustic Pattern Control

In order to effectively and flexibly control acoustic pattern, an efficient optimization design method of acoustic liquid lens (ALL) is developed by the frame of particle swarm optimization (PSO) algorithm. The ALL is composed of ethanol and dimethicone, and its parameters include ethanol concentration (EC), volume fraction of dimethicone (VFD), and total volume (TV). Based on the established finite element model and orthogonal design method, the data of acoustic pattern and ALL can be obtained by using COMSOL Multiphysics. Based on the simulation data, the neural network models are constructed to characterize the relationship between the parameters of ALL and the performance of acoustic pattern. The optimization design criteria of ALL are constructed based on the performance parameters of acoustic pattern, including focal distance (FD), transverse resolution (TR), and longitudinal resolution (LR). Based on the optimization criteria, the modified PSO algorithm is utilized to optimize the design parameters of ALL in the developed method. According to the desired FD, TR, and LR of acoustic pattern (20, 1, and 17 mm), the optimized EC, VFD, and TV of ALL are about 0.838, 0.165, and 164.4 [Formula: see text]. The performance parameters of acoustic pattern verified by simulation and experiments agree with the desired ones. In addition, using 6 MHz ultrasonic transducer with the optimized ALL, the ultrasonic imaging of tungsten wires and porcine eyeball further demonstrates the effectiveness and feasibility of the developed method.