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On the Statistical Distribution of Road Vehicle Vibrations

机译:道路车辆振动的统计分布

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This paper presents an alternative method for characterizing the random vibrations produced by transport vehicles. The paper discusses the significance and limitations of the average power spectral density and explains why it is not always adequate as the sole descriptor of road vehicle vibrations as the process generally tends to be non-stationary and non-Gaussian. The paper adopts an alternative analysis method, based on the statistical distribution of the moving root-mean-square (rms) vibrations, as a supplementary indicator of overall ride quality. A variety of sample vibration records, collected from various vehicle types and routes in Spain and Australia, were used to investigate the suitability of various mathematical models, based on the Weibull distribution. It shows that the model can also effectively describe the statistical parameters of the process, namely the mean, median, standard deviation, skewness and kurtosis. The paper proposes a single mathematical model that can accurately describe the statistical character of the non-stationary random vibrations generated by road vehicles in general. The proposed generic distribution model, based on the Weibull distribution, was developed to afford additional control over various aspects of the shape of the distribution function. The model was found to be general enough to be able to produce a range of well-known distributions. Curve-fitting results using the sum-of-squared error (least squares) optimization were found to produce non-convergent results, which required inclusion of the mean, median, standard deviation, skewness and kurtosis in the optimization algorithm. The paper also shows how the model is capable of accurately describing the statistical parameters of the process, namely the mean, median, standard deviation, skewness and kurtosis. This result is relevant not only for the characterization of ride quality but also for the accurate synthesis of road vehicle vibrations in the laboratory. The results can be used to assist in developing a novel method for simulating non-stationary (modulated) vibration in the laboratory. The rms distribution function can be used to create an rms level schedule that will enable the synthesis of random vibrations with varying rms levels to better represent the road transport vibration process.
机译:本文提出了一种表征运输车辆产生的随机振动的替代方法。本文讨论了平均功率谱密度的重要性和局限性,并解释了为什么它并不总是足够作为道路车辆振动的唯一描述者,因为该过程通常趋于非平稳且非高斯。本文基于移动均方根(rms)振动的统计分布,采用了一种替代分析方法,作为总体行驶质量的补充指标。根据威布尔分布,使用了从西班牙和澳大利亚的各种车辆类型和路线收集的各种样本振动记录,以研究各种数学模型的适用性。结果表明,该模型还可以有效地描述过程的统计参数,即均值,中位数,标准差,偏度和峰度。本文提出了一个单一的数学模型,可以准确地描述一般道路车辆产生的非平稳随机振动的统计特征。基于Weibull分布的拟议通用分布模型已开发,可以对分布函数形状的各个方面进行额外控制。发现该模型足够通用,能够产生一系列众所周知的分布。发现使用平方和误差(最小二乘法)优化的曲线拟合结果产生了非收敛结果,这需要在优化算法中包括均值,中位数,标准差,偏度和峰度。本文还展示了该模型如何能够准确描述过程的统计参数,即均值,中位数,标准差,偏度和峰度。该结果不仅与行驶质量的表征有关,而且与实验室中道路车辆振动的准确合成有关。结果可用于协助开发一种新颖的方法,用于模拟实验室中的非平稳(调制)振动。均方根分布函数可用于创建均方根水平计划,从而能够合成具有不同均方根水平的随机振动,以更好地表示道路运输振动过程。

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