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钢丝绳隔振器动态迟滞特性建模与参数识别研究

王红霞 陈大顶 戢玉莹

王红霞, 陈大顶, 戢玉莹. 钢丝绳隔振器动态迟滞特性建模与参数识别研究[J]. 机械科学与技术, 2020, 39(11): 1713-1719. doi: 10.13433/j.cnki.1003-8728.20190333
引用本文: 王红霞, 陈大顶, 戢玉莹. 钢丝绳隔振器动态迟滞特性建模与参数识别研究[J]. 机械科学与技术, 2020, 39(11): 1713-1719. doi: 10.13433/j.cnki.1003-8728.20190333
Wang Hongxia, Chen Dading, Ji Yuying. Research on Dynamic Hysteresis Modeling and Parameter Identification of a Wire-cable Vibration Isolator[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(11): 1713-1719. doi: 10.13433/j.cnki.1003-8728.20190333
Citation: Wang Hongxia, Chen Dading, Ji Yuying. Research on Dynamic Hysteresis Modeling and Parameter Identification of a Wire-cable Vibration Isolator[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(11): 1713-1719. doi: 10.13433/j.cnki.1003-8728.20190333

钢丝绳隔振器动态迟滞特性建模与参数识别研究

doi: 10.13433/j.cnki.1003-8728.20190333
基金项目: 

湖北省自然科学基金项目 2017CFB741

汽车动力传动与电子控制湖北省重点实验室(湖北汽车工业学院)项目 ZDK1201802

详细信息
    作者简介:

    王红霞(1977-), 副教授, 研究方向机械振动分析及控制理论和应用, 8784145@163.com

  • 中图分类号: TU112;TH113

Research on Dynamic Hysteresis Modeling and Parameter Identification of a Wire-cable Vibration Isolator

  • 摘要: 对钢丝绳隔振器的动态迟滞特性进行研究。针对小振幅下修正的归一化Bouc-wen模型拟合精度低的问题,在模型中引入一个关于激励位移的非线性函数,建立了隔振器动态迟滞特性模型;采用线性最小二乘法和带噪声统计估计器的自适应无迹卡尔曼滤波算法对模型参数进行识别。结果表明:建立的模型能够很好地描述钢丝绳隔振器动态迟滞特性,采用的参数识别方法可以准确有效地识别出模型参数,试验曲线和识别的模型拟合曲线吻合较好,验证了建立的模型和参数识别方法的有效性。
  • 图  1  测试试验

    图  2  动态响应试验迟滞环

    图  3  大振幅激励下试验与理论拟合迟滞曲线

    图  4  小振幅下激励试验与理论拟合迟滞曲线

    图  5  某一组参数下的纯迟滞力曲线

    图  6  恢复力试验迟滞环

    图  7  AUKF算法下试验与理论拟合迟滞环

    图  8  极限环方法下试验与理论拟合迟滞环

    图  9  模型改进前试验与理论迟滞环

    图  10  卸载阶段的误差与x/A的关系图

    图  11  加载阶段的误差与x/A的关系曲线

    图  12  模型改进后试验与理论迟滞环

    表  1  模型参数识别结果

    参数 N=3, M=2
    ke0 -20.704 2
    ke1 33.256 3
    ke2 1.975 2
    ke3 0.125 4
    kz0 73.527 6
    kz1 6.348 5
    kz2 -0.142 4
    ρ 1.647 1
    σ 2.456 2
    n 0.845 7
    下载: 导出CSV

    表  2  两种识别方法下的RMSE和RNL对比

    识别方法 预测迟滞环ERMSE/N 预测迟滞环RNL
    AUKF法 4.770 2 0.972 568
    极限环法 5.509 4 0.961 048
    下载: 导出CSV

    表  3  小振幅情况下模型改进前后RMSE和RNL对比

    振幅
    A/mm
    ERMSE RNL
    改进前 改进后 改进前 改进后
    1 9.648 6 0.932 565 4.309 5 0.980 462
    2 9.345 7 0.940 163 4.068 9 0.985 234
    下载: 导出CSV

    表  4  拟合函数参数数值

    加载f(x) 数值 卸载f(x) 数值
    a0* 12.890 a1 10.970
    a1* -1.834 a2 1.427
    a2* 1.051 a3 1.290
    a3* 0.188 a4 126.600
    a4* -1.400 b1 0.906
    a5* 0.820 b2 0.113
    b1* -4.462 b3 -0.213
    b2* 9.874 b4 -126
    b3* -9.702 c1 0.093
    b4* 6.168 c2 0.305
    b5* -2.280 c3 0.129
    ω 1.992 c4 72.080
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-08-16
  • 刊出日期:  2020-11-01

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