基于MR阻尼器复杂力学模型的参数高精度识别方法  

High-precision Parameter Identification Method Based on Complex Mechanical Model of MR Damper

作　　者：刘晓航 吴琼 牛再波 郭进 LIU Xiaohang;WU Qiong;NIU Zaibo;GUO Jin(School of Civil Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China)

机构地区：[1]石家庄铁道大学土木工程学院,河北石家庄050043

出　　处：《石家庄铁道大学学报(自然科学版)》2025年第1期104-111,118,共9页Journal of Shijiazhuang Tiedao University(Natural Science Edition)

基　　金：国家自然科学基金面上项目(52178493);河北省重点研发计划项目(21375402D);河北省自然科学基金面上项目(E2022210028);石家庄市科学技术局科研计划项目(231230025A)。

摘　　要：由于磁流变阻尼器(MRD)的力学特性,其模型中的某些参数必然与电流相关,且参数众多、耦合复杂,难以精准识别。为解决此问题,提出分步渐进式参数识别法,通过逐步识别和优化参数,提高电流相关参数的识别精度。在采用遗传算法识别磁流变阻尼器模型参数的基础上,进一步利用单变量敏感性分析法(OAAT)进行敏感性分析。通过评估各参数的敏感性和物理意义,依次优化模型参数,采用多项式回归方法拟合参数与电流的关系,并利用决定系数R 2来评估回归模型的拟合效果。结果表明,采用分步渐进式识别法得到的参数R 2值均超过98%,显著提高了参数识别精度。对参数识别的最终结果进行数值仿真,并与随机激励试验结果进行对比,以验证识别结果的准确性。结果表明,采用分步渐进式识别法得到的现象学模型仿真结果与试验数据高度吻合(fitnessall=0.0015),为类似研究提供了参考和借鉴。Due to the mechanical properties of magnetorheological dampers(MRD),some parameters in the model are inevitably related to the current.These parameters are numerous,interrelated and complex,making precise identification challenging.To address this issue,this paper proposed a step-by-step progressive parameter identification method,which enhances the accuracy of identifying current-related parameters through gradual identification and optimization.On the basis of using genetic algorithm to identify MRD model parameters,this study further utilized the One-At-A-Time(OAAT)sensitivity analysis method for sensitivity analysis.By evaluating the sensitivity and physical significance of each parameter,the model parameters are optimized sequentially.A polynomial regression method was then employed to fit the relationship between the parameters and the current,with the coefficient of determination(R 2)used to evaluate the fitting effect of the regression model.The results show that the R 2 values of the parameters obtained by using the step-by-step progressive identification method all exceed 98%,significantly improving the accuracy of parameter identification.Numerical simulations of the final identified parameters were performed and compared with the results of random excitation experiments to verify the accuracy of the identification results.The findings indicate that the phenomenological model simulation results obtained through the step-by-step progressive identification method are highly consistent with the experimental data(fitnessall=0.0015),provides valuable reference for similar research.

关 键 词：MR阻尼器 现象学模型 遗传算法 参数敏感性 OAAT法 参数识别 

分 类 号：U441[建筑科学—桥梁与隧道工程]