A DPIM-based probability analysis framework to obtain railway vehicle vibration characteristics considering the randomness of OOR wheel

IF 3 3区工程技术 Q2 ENGINEERING, MECHANICAL

Probabilistic Engineering Mechanics Pub Date : 2024-01-01 DOI:10.1016/j.probengmech.2024.103587

Tengfei Wang , Jinsong Zhou , Wenjing Sun , Dao Gong , Kai Zhou , Zhanfei Zhang , Zhixin Liu , Guoshun Li

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引用次数: 0

Abstract

The OOR (out-of-roundness) wheel is one of the main excitation sources causing vehicle vibration. However, the OOR wheel occurs randomly, indicating that the vibration behavior of a vehicle cannot be comprehensively evaluated using a deterministic approach. Thus, a probability analysis framework is proposed to obtain vehicle vibration characteristics while considering the randomness of the OOR wheel. The probability model of the random OOR wheel is derived by reducing the high-dimensional variables into a few independent variables of the radius, amplitude, and phase. Then, the vertical vehicle-track coupled system with OOR wheels is modelled. A DPIM (direct probability integral method) is further developed to analyze the evolution of excitation to response probabilities. Finally, the statistics of the random vibration of the vehicle are calculated. The proposed framework is verified using a numerical case. Results show that the PDF (probability density function) shape of the vehicle random vibration, induced by the Gaussian-distributed OOR wheel, deviates from the Gaussian distribution due to the nonlinear wheel/rail contact force. Instead, it exhibits a right-skewed shape, significantly impacting the dynamic performance. As the mean or coefficient of variation of the OOR wheel amplitude increases linearly, the reliability of the vehicle Sperling index experiences a quadratic or double-sloping decrease. Consequently, a maintenance threshold for OOR wheel amplitudes is given based on reliability considerations. Compared to Monte Carlo simulation, the proposed framework offers a computational efficiency improvement of at least one order of magnitude.

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基于 DPIM 的概率分析框架，用于获取考虑到 OOR 车轮随机性的铁路车辆振动特性

OOR（失圆）车轮是引起车辆振动的主要激励源之一。然而，OOR 车轮是随机出现的，这表明无法使用确定性方法对车辆的振动行为进行全面评估。因此，本文提出了一种概率分析框架，在考虑 OOR 车轮随机性的同时获取车辆振动特性。通过将高维变量简化为半径、振幅和相位等几个独立变量，得出了随机 OOR 车轮的概率模型。然后，对带有 OOR 轮的垂直车辆-轨道耦合系统进行建模。进一步开发了 DPIM（直接概率积分法）来分析激励到响应概率的演变。最后，计算车辆随机振动的统计数据。利用数值案例对所提出的框架进行了验证。结果表明，由高斯分布的 OOR 车轮诱发的车辆随机振动的 PDF（概率密度函数）形状偏离了高斯分布，这是由于车轮/轨道接触力的非线性造成的。相反，它呈现出右偏的形状，对动态性能产生了重大影响。当 OOR 轮振幅的平均值或变异系数线性增加时，车辆 Sperling 指数的可靠性会出现二次或双斜率下降。因此，基于可靠性考虑，给出了 OOR 车轮振幅的维护阈值。与蒙特卡罗模拟相比，所提出的框架至少提高了一个数量级的计算效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Probabilistic Engineering Mechanics 工程技术-工程：机械

CiteScore

3.80

自引率

15.40%

发文量

审稿时长

13.5 months

期刊介绍： This journal provides a forum for scholarly work dealing primarily with probabilistic and statistical approaches to contemporary solid/structural and fluid mechanics problems encountered in diverse technical disciplines such as aerospace, civil, marine, mechanical, and nuclear engineering. The journal aims to maintain a healthy balance between general solution techniques and problem-specific results, encouraging a fruitful exchange of ideas among disparate engineering specialities.