Parameter Identification and Linear Model of Giant Magnetostrictive Vibrator. (16th March 2021)
- Record Type:
- Journal Article
- Title:
- Parameter Identification and Linear Model of Giant Magnetostrictive Vibrator. (16th March 2021)
- Main Title:
- Parameter Identification and Linear Model of Giant Magnetostrictive Vibrator
- Authors:
- Wang, Anming
Meng, Jianjun
Xu, Ruxun
Li, Decang - Other Names:
- Vaidyanathan Sundarapandian Academic Editor.
- Abstract:
- 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 asAbstract : 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. … (more)
- Is Part Of:
- Discrete dynamics in nature and society. Volume 2021(2021)
- Journal:
- Discrete dynamics in nature and society
- Issue:
- Volume 2021(2021)
- Issue Display:
- Volume 2021, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 2021
- Issue:
- 2021
- Issue Sort Value:
- 2021-2021-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-03-16
- Subjects:
- System analysis -- Periodicals
Dynamics -- Periodicals
Chaotic behavior in systems -- Periodicals
Differentiable dynamical systems -- Periodicals
003.05 - Journal URLs:
- https://www.hindawi.com/journals/ddns/ ↗
- DOI:
- 10.1155/2021/6676911 ↗
- Languages:
- English
- ISSNs:
- 1026-0226
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 16395.xml