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Parameter Identification and Linear Model of Giant Magnetostrictive Vibrator

Author

Listed:
  • Anming Wang
  • Jianjun Meng
  • Ruxun Xu
  • Decang Li
  • Sundarapandian Vaidyanathan

Abstract

A linear magnetization model is built to replace the Jiles–Atherton model in order to describe the relationship between the magnetic field intensity and the magnetization intensity of the giant magnetostrictive vibrator (GMV). The systematic modeling of the GMV is composed of three aspects, i.e., the structural mechanic model, the magnetostrictive model, and the Jiles–Atherton model. The Jiles–Atherton model has five parameters to be defined; hence, its solution is so complex that it is not convenient in application. Therefore, the immune genetic algorithm (IGA) is applied in the identification of the five parameters of the Jiles–Atherton model and it showed a higher stability compared with the identification result of the differential evolution algorithm (DEA). The identification parameters of the two algorithms were employed, respectively, to calculate the excitation force and it was found that the relative error of IGA was evidently smaller than that of DEA, indicating that the former was more reliable than the latter. According to the identification results of IGA and based on the least square method (LSM), curve-fittings to the magnetic field intensity and magnetization intensity were conducted by using the linear function. And the linear magnetization model was built to replace the Jiles–Atherton model. Research results show that the linear model of the GMV can be established by combining the linear magnetization model with the structural mechanic model as well as the giant magnetostrictive model. The linear magnetization model, which has great engineering application value, can be applied in the open-loop control of the vibrator.

Suggested Citation

  • Anming Wang & Jianjun Meng & Ruxun Xu & Decang Li & Sundarapandian Vaidyanathan, 2021. "Parameter Identification and Linear Model of Giant Magnetostrictive Vibrator," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-15, March.
  • Handle: RePEc:hin:jnddns:6676911
    DOI: 10.1155/2021/6676911
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