Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification

Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement hysteretic curve. The Gamultiobj algorithm and the g...

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Autores principales:	Junzhe Lin, Zhihong Niu, Xufang Zhang, Hui Ma, Yulai Zhao, Qingkai Han
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Hysteresis model parameter identification clamp nonlinear Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/e4d0e52c8d4a4b9383f7071d1ceecf57
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spelling	oai:doaj.org-article:e4d0e52c8d4a4b9383f7071d1ceecf572021-11-18T00:11:21ZClamp Nonlinear Modeling and Hysteresis Model Parameter Identification2169-353610.1109/ACCESS.2021.3123469https://doaj.org/article/e4d0e52c8d4a4b9383f7071d1ceecf572021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9590490/https://doaj.org/toc/2169-3536Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement hysteretic curve. The Gamultiobj algorithm and the group search optimization (GSO) algorithm are used to fit and identify the material softening and hardening hysteresis curves, respectively. The effectiveness of the optimization algorithm for identifying the parameters of the hysteretic model is verified, and the optimization effects of the two algorithms are compared. The results show that the Gamultiobj algorithm has better parameter identification ability and curve fitting ability for the hysteretic model. Then, the hysteresis curve describing the nonlinear characteristics of a clamp is obtained through the static stiffness experiment of the clamp. The experimental curve is fitted by the Gamultiobj algorithm. As a result, the nonlinear Bouc-Wen model parameters of the clamp are obtained, and the stiffness and damping of the clamp are recognized. The distribution statistics of the obtained parameters are performed, and it is found that each parameter satisfies a certain probability distribution, which indicates that the parameter identification result is reasonable.Junzhe LinZhihong NiuXufang ZhangHui MaYulai ZhaoQingkai HanIEEEarticleHysteresis modelparameter identificationclampnonlinearElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 147757-147767 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Hysteresis model parameter identification clamp nonlinear Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Hysteresis model parameter identification clamp nonlinear Electrical engineering. Electronics. Nuclear engineering TK1-9971 Junzhe Lin Zhihong Niu Xufang Zhang Hui Ma Yulai Zhao Qingkai Han Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
description	Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement hysteretic curve. The Gamultiobj algorithm and the group search optimization (GSO) algorithm are used to fit and identify the material softening and hardening hysteresis curves, respectively. The effectiveness of the optimization algorithm for identifying the parameters of the hysteretic model is verified, and the optimization effects of the two algorithms are compared. The results show that the Gamultiobj algorithm has better parameter identification ability and curve fitting ability for the hysteretic model. Then, the hysteresis curve describing the nonlinear characteristics of a clamp is obtained through the static stiffness experiment of the clamp. The experimental curve is fitted by the Gamultiobj algorithm. As a result, the nonlinear Bouc-Wen model parameters of the clamp are obtained, and the stiffness and damping of the clamp are recognized. The distribution statistics of the obtained parameters are performed, and it is found that each parameter satisfies a certain probability distribution, which indicates that the parameter identification result is reasonable.
format	article
author	Junzhe Lin Zhihong Niu Xufang Zhang Hui Ma Yulai Zhao Qingkai Han
author_facet	Junzhe Lin Zhihong Niu Xufang Zhang Hui Ma Yulai Zhao Qingkai Han
author_sort	Junzhe Lin
title	Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
title_short	Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
title_full	Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
title_fullStr	Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
title_full_unstemmed	Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification
title_sort	clamp nonlinear modeling and hysteresis model parameter identification
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/e4d0e52c8d4a4b9383f7071d1ceecf57
work_keys_str_mv	AT junzhelin clampnonlinearmodelingandhysteresismodelparameteridentification AT zhihongniu clampnonlinearmodelingandhysteresismodelparameteridentification AT xufangzhang clampnonlinearmodelingandhysteresismodelparameteridentification AT huima clampnonlinearmodelingandhysteresismodelparameteridentification AT yulaizhao clampnonlinearmodelingandhysteresismodelparameteridentification AT qingkaihan clampnonlinearmodelingandhysteresismodelparameteridentification
_version_	1718425195800166400

Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification

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