Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization

Complex material parameters that can represent the losses of giant magnetostrictive materials (GMMs) are the key parameters for high-power transducer design and performance analysis. Since the GMMs work under pre-stress conditions and their performance is highly sensitive to pre-stress, the complex...

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Autores principales:	Yukai Chen, Xin Yang, Mingzhi Yang, Yanfei Wei, Haobin Zheng
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	giant magnetostrictive material complex parameters losses transducer lumped parameter model particle swarm optimization (PSO) algorithm Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/7b62f955b26043629aaa877e191b6d21
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spelling	oai:doaj.org-article:7b62f955b26043629aaa877e191b6d212021-11-25T18:23:51ZCharacterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization10.3390/mi121114162072-666Xhttps://doaj.org/article/7b62f955b26043629aaa877e191b6d212021-11-01T00:00:00Zhttps://www.mdpi.com/2072-666X/12/11/1416https://doaj.org/toc/2072-666XComplex material parameters that can represent the losses of giant magnetostrictive materials (GMMs) are the key parameters for high-power transducer design and performance analysis. Since the GMMs work under pre-stress conditions and their performance is highly sensitive to pre-stress, the complex parameters of a GMM are preferably characterized in a specific pre-stress condition. In this study, an optimized characterization method for GMMs is proposed using three complex material parameters. Firstly, a lumped parameter model is improved for a longitudinal transducer by incorporating three material losses. Then, the structural damping and contact damping are experimentally measured and applied to confine the parametric variance ranges. Using the improved lumped parameter model, the real parts of the three key material parameters are characterized by fitting the experimental impedance data while the imaginary parts are separately extracted by the phase data. The global sensitivity analysis that accounts for the interaction effects of the multiple parameter variances shows that the proposed method outperforms the classical method as the sensitivities of all the six key parameters to both impedance and phase fitness functions are all high, which implies that the extracted material complex parameters are credible. In addition, the stability and credibility of the proposed parameter characterization is further corroborated by the results of ten random characterizations.Yukai ChenXin YangMingzhi YangYanfei WeiHaobin ZhengMDPI AGarticlegiant magnetostrictive materialcomplex parameterslossestransducerlumped parameter modelparticle swarm optimization (PSO) algorithmMechanical engineering and machineryTJ1-1570ENMicromachines, Vol 12, Iss 1416, p 1416 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	giant magnetostrictive material complex parameters losses transducer lumped parameter model particle swarm optimization (PSO) algorithm Mechanical engineering and machinery TJ1-1570
spellingShingle	giant magnetostrictive material complex parameters losses transducer lumped parameter model particle swarm optimization (PSO) algorithm Mechanical engineering and machinery TJ1-1570 Yukai Chen Xin Yang Mingzhi Yang Yanfei Wei Haobin Zheng Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
description	Complex material parameters that can represent the losses of giant magnetostrictive materials (GMMs) are the key parameters for high-power transducer design and performance analysis. Since the GMMs work under pre-stress conditions and their performance is highly sensitive to pre-stress, the complex parameters of a GMM are preferably characterized in a specific pre-stress condition. In this study, an optimized characterization method for GMMs is proposed using three complex material parameters. Firstly, a lumped parameter model is improved for a longitudinal transducer by incorporating three material losses. Then, the structural damping and contact damping are experimentally measured and applied to confine the parametric variance ranges. Using the improved lumped parameter model, the real parts of the three key material parameters are characterized by fitting the experimental impedance data while the imaginary parts are separately extracted by the phase data. The global sensitivity analysis that accounts for the interaction effects of the multiple parameter variances shows that the proposed method outperforms the classical method as the sensitivities of all the six key parameters to both impedance and phase fitness functions are all high, which implies that the extracted material complex parameters are credible. In addition, the stability and credibility of the proposed parameter characterization is further corroborated by the results of ten random characterizations.
format	article
author	Yukai Chen Xin Yang Mingzhi Yang Yanfei Wei Haobin Zheng
author_facet	Yukai Chen Xin Yang Mingzhi Yang Yanfei Wei Haobin Zheng
author_sort	Yukai Chen
title	Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
title_short	Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
title_full	Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
title_fullStr	Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
title_full_unstemmed	Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization
title_sort	characterization of giant magnetostrictive materials using three complex material parameters by particle swarm optimization
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7b62f955b26043629aaa877e191b6d21
work_keys_str_mv	AT yukaichen characterizationofgiantmagnetostrictivematerialsusingthreecomplexmaterialparametersbyparticleswarmoptimization AT xinyang characterizationofgiantmagnetostrictivematerialsusingthreecomplexmaterialparametersbyparticleswarmoptimization AT mingzhiyang characterizationofgiantmagnetostrictivematerialsusingthreecomplexmaterialparametersbyparticleswarmoptimization AT yanfeiwei characterizationofgiantmagnetostrictivematerialsusingthreecomplexmaterialparametersbyparticleswarmoptimization AT haobinzheng characterizationofgiantmagnetostrictivematerialsusingthreecomplexmaterialparametersbyparticleswarmoptimization
_version_	1718411207219609600

Characterization of Giant Magnetostrictive Materials Using Three Complex Material Parameters by Particle Swarm Optimization

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