Admittance Circular Series Resonance Tracking Based On BP Neural Network

Xinhui Wang, Niansong Zhang, Yu Fu, Aimin Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The ultrasonic processing system includes an ultrasonic power supply, an ultrasonic transducer and a horn. In the whole ultrasonic machining system, the ultrasonic power supply plays a vital role, which determines the amplitude stability of the tool machining, the output efficiency of the ultrasonic transducer and the surface quality of the workpiece. Therefore, a fast and accurate series resonant frequency tracking algorithm is the key to ultrasonic power supply. In this paper, the resonant frequency of the transducer is tracked by the phase difference, and the series resonant frequency is obtained based on the resonant frequency point using the admittance circle characteristic of the transducer. In the process of finding the series resonance frequency, BP neural network is used to predict the dynamic resistance of the transducer. This method can not only quickly obtain the change of the dynamic resistance but also has a relatively high precision.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Mechatronics and Automation, ICMA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages303-308
Number of pages6
ISBN (Electronic)9781665408523
DOIs
Publication statusPublished - 2022
Event19th IEEE International Conference on Mechatronics and Automation, ICMA 2022 - Guilin, Guangxi, China
Duration: 7 Aug 202210 Aug 2022

Publication series

Name2022 IEEE International Conference on Mechatronics and Automation, ICMA 2022

Conference

Conference19th IEEE International Conference on Mechatronics and Automation, ICMA 2022
Country/TerritoryChina
CityGuilin, Guangxi
Period7/08/2210/08/22

Keywords

  • Admittance circle
  • BP neural network
  • ultrasonic power supply
  • ultrasonic transducer

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