机床与液压2024,Vol.52Issue(4) :126-131.DOI:10.3969/j.issn.1001-3881.2024.04.021

基于最小二乘法和BP神经网络的磁流变阻尼器H-B模型参数辨识方法

Parameter Identification Method of H-B Model for Magnetorheological Damper Based on Least Square Method and BP Neural Network

张忠奎 张晗 闫洋洋
机床与液压2024,Vol.52Issue(4) :126-131.DOI:10.3969/j.issn.1001-3881.2024.04.021

基于最小二乘法和BP神经网络的磁流变阻尼器H-B模型参数辨识方法

Parameter Identification Method of H-B Model for Magnetorheological Damper Based on Least Square Method and BP Neural Network

张忠奎 1张晗 2闫洋洋1
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作者信息

  • 1. 潍坊科技学院山东省高校设施园艺实验室,山东潍坊 262700
  • 2. 深圳迈瑞生物医疗电子股份有限公司,广东深圳 518055
  • 折叠

摘要

针对Bingham模型磁流变阻尼器由于剪切稀化效应带来的阻尼力计算误差,在理论和仿真分析的基础上,提出一种最小二乘法和BP神经网络相结合的方法,对磁流变阻尼器H-B模型进行参数辨识,获得各参数与电流的关系,从而对磁流变阻尼器的阻尼力进行准确计算.最后通过磁流变阻尼器实验对理论方法进行验证.结果表明:借助于磁流变阻尼器的仿真分析,最小二乘法和BP神经网络相结合的磁流变阻尼器H-B模型参数辨识方法精确度高、吻合性好,验证了参数辨识结果的通用性及准确性.

Abstract

In view of the calculation error of damping force caused by shear thinning effect of Bingham model magnetorheological(MR)damper,a method combining least square method and BP neural network was proposed on the basis of theoretical and simulation analysis to identify the parameters of H-B model of magnetorheological damper,the relationship between parameters and current were obtained,and the damping force of magnetorheological damper was accurately calculated.Finally,the theoretical method was verified by the experiment of magnetorheological damper.The results show that:with the help of the simulation analysis of magnetorheological damp-er,the H-B model parameter identification method of magnetorheological damper with the combination of least square method and BP neural network has high accuracy and good coincidence,which verifies the universality and accuracy of the parameter identification re-sults.

关键词

磁流变液阻尼器/H-B模型/最小二乘法/BP神经网络

Key words

magnetorheological fluid damper/H-B model/least square method/BP neural network

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基金项目

潍坊科技学院学科建设项目(2021XKJS25)

出版年

2024
机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
参考文献量20
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