基于傅里叶逆变换的三维随机路面建模与仿真
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作者单位:

1.武汉科技大学 机械自动化学院,黄冈师范学院 机电与汽车工程学院;2.武汉科技大学 机械自动化学院;3.黄冈师范学院 机电与汽车工程学院;4.哈尔滨工业大学 交通科学与工程学院

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中图分类号:

U461.51

基金项目:

国家自然科学基金(51778509,51827812);湖北省自然科学基金(2018CFB293)


Modeling and Simulation of 3D Stochastic Pavement Based on Inverse Fourier Transform
Author:
Affiliation:

1.School of Machinery and Automation,Wuhan University of Science and Technology;2.School of Electromechanical and Automobile Engineering,Huanggang Normal University;3.School of Transportation Science and Technology,Harbin Institute of Technology

Fund Project:

National Natural Science Foundation of China(51778509,51827812);Hubei Provincial Natural Science Foundation of China(2018CFB293)

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    摘要:

    为了满足工程中虚拟实验的需求,研究了利用功率谱密度函数的三维随机路面不平度建模方法。利用国家标准中采用的幂函数道路谱拟合公式,推导出路面的二维功率谱解析表达式,避免了有理函数法的参数估计问题。建立了二维傅里叶逆变换法生成三维随机路面的流程;并以某汽车振动系统所关注性能需求,仿真了国标中的E级路面;分别采用周期图法和AR参数模型法估计了仿真路面的功率谱。结果表明,仿真生成的路面与标准路面谱是高度一致的,基于二维离散傅里叶逆变换的方法不仅准确而且快速,有较强的实用性。

    Abstract:

    In order to meet the needs of virtual experiment in engineering, a 3D stochastic road roughness modeling method using power spectral density function is studied. By using the road spectrum fitting formula of power function adopted in national standard, the analytical expression of two-dimensional power spectrum of road surface is derived, which avoids the parameter estimation problem of rational function method. The process of generating 3D stochastic pavement by two-dimensional inverse Fourier transform is established, and the E-grade pavement in the national standard is simulated by the performance requirements of a certain automobile vibration system. The power spectrum of the simulated pavement is estimated by using periodogram method and AR parameter model method respectively.The estimated results show that the simulated pavement spectrum is highly consistent with the standard pavement spectrum.,and the method based on two-dimensional inverse discrete Fourier transform is not only accurate and fast, but also has strong practicability.

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历史
  • 收稿日期:2019-09-17
  • 最后修改日期:2019-09-27
  • 录用日期:2019-10-08
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