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Nonlinear Gear Transmission System Numerical Dynamic Analysis and Experimental Validation

机译:非线性齿轮传动系统数值动态分析与实验验证

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The main objective of the present work was to accurately predict the dynamic response of a gear transmission system. First, a nonlinear mathematical model is introduced. In this model, the housing of the gearbox is modeled by using finite elements, while the essential effects of the gear-pair, the bearings and the shafts are taken into account via a lumped nonlinear mathematical model. This model possesses strongly nonlinear characteristics, accounting for gear backlash, meshing stiffness, transmission error properties and bearing stiffness nonlinearities. Then, a Bayesian uncertainty quantification and propagation (UQ&P) framework is adopted in order to estimate the optimal values of the gearbox, gear-pair and bearing model parameters. In order to identify the values of the parameters, accelerations time histories are used, obtained during various operating conditions of the gearbox. These measurements are recorded from a special experimental device, which was designed and set up for this purpose. The effect of correlation in the prediction error models postulated in the Bayesian model selection and parameter estimation technique is investigated. Finally the experimental results was compared to those from the numerical model for verification of the numerical procedure and improvement of the numerical modeling of the gear transmission components.
机译:本工作的主要目的是准确地预测齿轮传动系统的动态响应。首先,介绍了非线性数学模型。在该模型中,通过使用有限元件建模齿轮箱的壳体,而齿轮对,轴承和轴的基本效果是通过集总线的非线性的数学模型考虑的。该型号具有强烈的非线性特性,占齿轮间隙,啮合刚度,透射误差性和轴承刚度非线性。然后,采用贝叶斯不确定性量化和传播(UQ&P)框架,以估计变速箱,齿轮对和轴承模型参数的最佳值。为了识别参数的值,使用加速时间历史,在变速箱的各种操作条件期间获得。这些测量从特殊的实验装置记录,为此目的而设计和设置。研究了在贝叶斯模型选择和参数估计技术中假设的预测误差模型中的相关性的影响。最后将实验结果与来自数值模型的数值模型进行比较,以及齿轮传动组件的数值模拟的改进。

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