Intelligent Optimization of Matching Layers for Piezoelectric Ultrasonic Transducer

Abstract

The performance of piezoelectric ultrasonic transducer (PUT) is obviously affected by its matching layer. An intelligent optimization method for matching layer of PUT is proposed to fabricate PUT with high performance. The original data, including matching layer and performance parameters of PUT, is obtained by PiezoCAD software. Then the neural network models are established to mathematically characterize the effect of matching layer on the performance of PUT. The optimization criteria for PUT is constructed according to its performance requirements, such as center frequency (CF), bandwidth (BW) and pulse width (PW). In order to decrease the material cost, the thicknesses of matching layers are also considered in the optimization criteria. The modified particle swarm optimization algorithm is used to optimize the thicknesses of matching layers (Ag-epoxy and Parylene C). According to the designed performance, the optimized thicknesses of Ag-epoxy and Parylene C are about $54~\mu \text{m}$ and $21~\mu \text{m}$ , respectively. Based on the optimized thicknesses of matching layers, the simulated and experimental performances of PUT well agree with the designed ones. In addition, compared to the traditional quarter-wavelength theory, the proposed method can effectively decrease the materials cost. The −6dB BW and PW of PUT fabricated according to the optimized parameters are about 68.5% and $0.123~\mu \text{s}$ , which are better than that fabricated according to the quarter-wavelength theory (about 50% and $0.147~\mu \text{s}$ ).