基于单自由度参数激励模型的车辆随机振动分析

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摘要包装件振动可靠性的分析和优化需要构建高效准确的车辆随机振动载荷分析模型。本文将车辆建模为单自由度参数激励系统，分析车辆在平稳载荷下的加速度响应。基于Mathieu方程分析车辆动态响应特性，结果表明，车辆响应中出现少量的大幅振动响应的原因是参数激励系统中随机过程β(t)的波动引起了系统的失稳。分别构建车辆在稳态、失稳和衰减条件下的响应分析方法，建立了车辆加速度响应的概率密度函数分析方法，构建了根据记录的实验数据识别系统参数的方法。分析结果表明，本文建立的车辆随机振动分析方法能够高效准确地再现车辆非平稳随机振动的时域特征及概率密度函数，为研究包装件振动可靠性提供了高效准确的分析基础。

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	朱大鹏1
	薛如壮1
	曹兴潇2

关键词 ：包装件振动可靠性分析, 参数激励模型, Mathieu方程, 系统参数识别

Abstract：Analytical model for vehicle vibration with efficiency and accuracy is essential for package vibration reliability analysis and optimization. In this paper, vehicle was modeled as a single degree of freedom parametric excitation system, acceleration response of the vehicle excited by stationary loads was analyzed. The response characterization of the parametric system was approximated analytically by use of Mathieu’s equation, from the analysis, it can be observed that the fluctuation of stochastic process β(t) may give rise to the instability of vehicle response, which is the intrinsic reason to the rare large-altitude response of vehicle. The analysis methods for vehicle response under steady condition, instability condition and decay condition were proposed respectively, the parameter identification procedure for the parametric excitation system was also given. The simulation results indicated that one can simulate vehicle vibration accurately using the proposed parametric excitation model, which have good agreements with the experimental data in time domain manner and PDF manner. The model also provides an analytical basis for accurate and efficient research on package vibration reliability analysis.

Key words： package vibration reliability analysis parametric excitation model Mathieu’s equation system parameters identification

收稿日期: 2020-09-08 出版日期: 2022-01-28

引用本文:

朱大鹏1，薛如壮1，曹兴潇2. 基于单自由度参数激励模型的车辆随机振动分析[J]. 振动与冲击, 2022, 41(2): 79-86.
ZHU Dapeng1，XUE Ruzhuang1，CAO Xingxiao2. Vehicle random vibration analysis using a SDOF parametric excitation model. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(2): 79-86.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I2/79

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