Determination of elastic loss of piezoelectric materials by impedance curve fitting using intelligent algorithms

Abstract

Understanding the loss parameters of piezoelectric materials is crucial for designing effective piezoelectric sensors. Traditional measurement techniques to obtain the elastic loss parameters are primarily through three methods, the 3dB bandwidth, impedance fitting ways and ultrasonic attenuation. However, the elastic loss obtained using these three methods are all constant and frequency-independent. Therefore, a fast and accurate method is needed to acquire the elastic loss of piezoelectric materials. This paper introduces a novel approach for calculating elastic loss parameters using impedance curve fitting using intelligent algorithms. A frequency-dependent second-order elastic loss model of piezoelectric material is established. Then, genetic algorithms are introduced to acquire the optimal elastic loss parameters. Results show excellent agreement between theoretical and experimental impedance, with less than a 5% error. elastic loss parameters obtained through impedance curve using intelligent algorithms match those from stress experiments, with an error of less than 6%. This method offers a rapid, precise, and cost-effective approach to obtain frequency-dependent second-order elastic loss parameters of piezoelectric materials.