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基于等效电路模型的超声波电机串联谐振频率识别方法OACSTPCD

A Series Resonant Frequency Identification Method for Ultrasonic Motors Based on Equivalent Circuit Model

中文摘要英文摘要

在超声波电机运行过程中,由于负载、温升等因素的影响,电机的串联谐振频率会发生漂移.为了对电 机进行精确控制,需要准确识别并跟踪电机的串联谐振频率.基于超声波电机的Butterworth-Van Dyke(BVD)等效电路模型,提出电机的串联谐振频率识别方法.利用电机端电压和端电流作为反馈信号,对反馈信号进行处理得到差分电压,进而得到电机端电压与差分电压的相位差,并分析了该相位差与串联谐振频率的关系.在此基础上,设计了相应的电路实现方案,制作了电路实物,采用所提出的方法对样机的串联谐振频率进行识别,并用阻抗分析仪测量了样机的串联谐振频率.结果表明:利用所提出的方法识别得到的串联谐振频率与试验测量得到的串联谐振频率相吻合,证明所提出的超声波电机串联谐振频率识别方法的准确性.

During the operation of ultrasonic motors,the series resonant frequency of the motor may drift due to factors such as load and temperature rise.In order to achieve precise control of the motor,it is necessary to accurately identify and track the series resonant frequency of the motor.A series resonant frequency identification method for ultrasonic motors based on Butterworth-Van Dyke(BVD)equivalent circuit model of the motor is proposed.The driving voltage and current of the motor are used as feedback signals,which are then processed to obtain a differential voltage.The phase difference between the driving voltage and the differential voltage is compared.And the relationship between the phase difference and the series resonant frequency is analyzed.A circuit implementation scheme is designed and a physical circuit is manufactured.The series resonant frequency of the prototype motor is then identified with the proposed method.Moreover,the series resonant frequency of the motor is also measured with impedance analyzer.The result shows that the frequency identified with the proposed method is in good agreement with the measured one,which verifies the accuracy of the proposed series resonant frequency identification method for ultrasonic motors.

蒋春容;徐耀耀;成苏南;濮阳鹏昊

南京工程学院电力工程学院,江苏南京 211167

动力与电气工程

超声波电机串联谐振频率等效电路频率识别

ultrasonic motorseries resonant frequencyequivalent circuitfrequency identification

《电机与控制应用》 2024 (008)

76-84 / 9

国家自然科学基金项目(51777029);南京工程学院校级科研基金项目(CKJB202103)National Natural Science Foundation of China(51777029);Scientific Research Fund of Nanjing Institute of Technology(CKJB202103)

10.12177/emca.2024.079

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