Dynamics and Fatigue Analysis of Planetary Gear Trains under Random Loading

行星轮系(PGTS)在工业等领域有着广泛的应用。在一些应用中，PGT承受的载荷是随机的。风能行业的风力发电机组和石油天然气行业的定向钻井是两种具有代表性的以PGT为输电单元、承受随机载荷的场景。这些系统的振动引起的疲劳是工业中的一个突出问题，具有巨大的经济后果。然而，振动应力的随机性在很大程度上阻碍了准确的疲劳预测和适当的疲劳管理。*本研究旨在系统地研究在随机载荷作用下的钢管混凝土结构的动力学特性，并开发有效的疲劳预测方法。基于上述两种情况，将所有PGT共用的内部激励和因应用不同而不同的外部激励建模为随机过程。对于目前所知甚少的钻井过程中的外部激励，将进行实验研究。然后用数值方法和解析方法求解结构响应的统计量，包括位移、速度、应力和应变。这些统计信息构成了进一步疲劳预测的基础。希望通过本文的研究，能够提高风电机组和钻井平台的可靠性和疲劳寿命。我们的长期目标是在一般的随机环境下建立一个关于PGTS随机动力学的理论框架，从而使该方法和算法能够应用于更广泛的应用，例如在海洋工程和陆地交通工具中的应用。*

Planetary Gear Trains (PGTs) are widely used in industry and many other applications. In some of the applications, the loads to which the PGTs are subjected are random/stochastic. Two representative scenarios where PGTs are used as a transmission unit, and subjected to random loads include wind turbines in wind energy industry and directional drilling in oil and gas industry. Fatigue caused by the vibration in these systems is a outstanding issue in the industries, and has huge economical consequence. However, the random nature of the vibration stresses largely hinders accurate fatigue prediction and proper fatigue management. ***The proposed research intends to systematically investigate the dynamics of PGTs under random loads, and develop effective fatigue prediction methods. Based on the two cases above, the internal excitations which are common to all PGTs and the external excitations which vary for different applications will be modeled as random processes. Experiments will be carried out to characterize the external excitation in drilling for which little is known at present. Then the statistics of the responses, including displacement, velocity, stresses and strains, could be solved for with numerical and analytic methods. These statistic information constitutes the basis for further fatigue prediction. It is expected that, through this proposed research, the reliability and fatigue life of PGTs in both wind turbines and drilling could be improved. The long term goal is to develop a theoretical framework for random dynamics of PGTs in general random context; thus, the method and algorithms can be applied to and benefit broader applications, such as applications in off-shore engineering and land vehicles.  *** **