%0 Journal Article %T 基于非定常机电转换系数的超磁致伸缩换能器输出振幅模型<br>Equivalent amplitude model for a giant magnetostrictive transducer based on an unsteady electromechanical conversion coefficient %A 蔡万宠 %A 张建富 %A 郁鼎文 %A 吴志军 %A 冯平法 %J 清华大学学报(自然科学版) %D 2017 %R 10.16511/j.cnki.qhdxxb.2017.22.021 %X 为实现对超磁致伸缩超声换能器输出振幅的准确预测,由换能器的等效电路推导得到输出振幅模型,并通过阻抗分析辨识出模型中的等效参数。为提高模型的准确性,研究了激励信号的频率和电压幅值对机电转换系数的影响。通过实验建立机电转换系数与激励频率的关系曲线,插值得到不同频率激励下换能器的机电转换系数,由振幅模型得到换能器输出振幅与激励电流幅值的关系曲线。结果表明:基于阻抗分析结果建立的振幅模型能够较准确地预测换能器在谐振状态下的输出振幅,验证了振幅模型的正确性。基于插值法得到的振幅-电流幅值曲线与实验结果一致,验证了所建立的机电转换系数与激励频率之间关系的正确性,提高了振幅模型在不同频率下的准确性。<br>Abstract:The vibration amplitude model of a giant magnetostrictive transducer was established using an equivalent circuit of the transducer. The model parameters were identified through an impedance analysis. The accuracy of the vibration amplitude model was improved by analyzing the effects of the frequency and amplitude of the excitation voltage on the electromechanical conversion coefficient. The relation between the excitation frequency and the electromechanical conversion coefficient was obtained experimentally. Then, the electromechanical conversion coefficient was calculated for various frequencies using interpolation to relate the vibration amplitude to the excitation current. Comparison with experimental results shows that the vibration amplitude model determined by the impedance analysis can be used to predict the transducer vibration at resonance. The interpolated electromechanical conversion coefficients can be used to calculate the vibration amplitudes so that the theoretical relations between the amplitude and the current for different excitation frequencies are consistent with experimental results, which indicates that the model has the proper relationships between the electromechanical conversion coefficient and the excitation frequency. %K 超磁致伸缩换能器 %K 振幅模型 %K 机电转换系数 %K 等效电路 %K < %K br> %K giant magnetostrictive transducer %K amplitude model %K electromechanical conversion coefficient %K equivalent circuit %U http://jst.tsinghuajournals.com/CN/Y2017/V57/I5/459