Gear wear becomes one of the important reasons for the fault of gear systems by causing tooth surface geometric deviations, changing time-varying mesh stiffness (TVMS), and increasing unloaded static transmission error (USTE). However, existing wear prediction models ignore the effects of friction and tooth profile parameter updates, which inevitably leads to unclear research on dynamic analysis. Based on the Archard equation, this work proposes a real-time iterative update model to calculate the wear evolution process with equivalent curvature radius updates. Subsequently, an improved friction-wear coupling model is developed to calculate the wear depth, TVMS, and USTE, with an iterative solution process based on the updating of friction and wear coefficients, and the load sharing factor (LSF). The effectiveness of the improved model is verified by wear experiments and finite element analysis. Based on the tribo-dynamic model of the gear-rotor-bearing systems, the dynamic characteristics considering friction-wear coupling are studied. The results indicate that the effect of friction intensifies as the speed decreases, while increased wear amplifies vibrations at most speeds, exacerbates meshing shocks, and initially expands then contracts the chaotic speed range. This work provides strong theoretical support for predicting wear depth and understanding gear wear behavior.

中文翻译：

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考虑齿轮系统摩擦磨损耦合的动力学建模与分析

齿轮磨损引起齿面几何偏差、改变时变啮合刚度（TVMS）、增大空载静态传动误差（USTE），成为齿轮系统故障的重要原因之一。然而，现有的磨损预测模型忽略了摩擦和齿廓参数更新的影响，这不可避免地导致动态分析研究的不明确。基于Archard方程，本文提出了一种实时迭代更新模型，以计算等效曲率半径更新的磨损演化过程。随后，开发了一种改进的摩擦磨损耦合模型来计算磨损深度、TVMS 和 USTE，并采用基于摩擦和磨损系数以及负载共享因子 (LSF) 更新的迭代求解过程。通过磨损实验和有限元分析验证了改进模型的有效性。基于齿轮-转子-轴承系统的摩擦动力学模型，研究了考虑摩擦磨损耦合的动态特性。结果表明，摩擦效应随着速度降低而加剧，而磨损的增加会放大大多数速度下的振动，加剧啮合冲击，并且最初扩大然后缩小混沌速度范围。这项工作为预测磨损深度和理解齿轮磨损行为提供了强有力的理论支持。