A novel analytical model for evaluating the time-varying meshing stiffness of helical gears under irregular pitting failure

IF 2.2 3区 工程技术 Q2 MECHANICS
Zong Meng, Xiushen Pang, Guoqing Hao, Yesen Jin, Jimeng Li, Fengjie Fan
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引用次数: 1

Abstract

Helical gear teeth are subject to spalling, pitting and other failures under prolonged operation, which can contribute to a reduction in the time-varying meshing stiffness (TVMS) of the gear. The shape of the depression formed by the absence of the gear tooth surface is irregular in practice. Firstly, an irregular-shaped pitting model is constructed by the slicing method. On the premise of improving the transition curve, the TVMS calculation equations under the irregular pitting model are derived considering the effect of axial stiffness. Then, a randomly distributed tooth surface pitting evolution model was established by the random pitting generation function, and the effects of three different failure degrees from slight to severe pitting on the TVMS are evaluated. Eventually, the faulty helical gear pairs are constructed in Solidworks and simulated by the finite element method (FEM), verifying that the irregular pitting evolution model and calculation method proposed in this paper are effective.

Abstract Image

一种评估不规则点蚀下斜齿轮时变啮合刚度的新分析模型
斜齿轮轮齿在长时间运行时会出现剥落、点蚀和其他故障,这可能导致齿轮的时变啮合刚度(TVMS)降低。在实践中,由于缺少齿轮齿表面而形成的凹陷的形状是不规则的。首先,采用切片法建立了不规则形状点蚀模型。在改进过渡曲线的前提下,推导了考虑轴向刚度影响的不规则点蚀模型下的TVMS计算方程。然后,利用随机点蚀生成函数建立了随机分布的齿面点蚀演化模型,并评价了从轻微点蚀到严重点蚀的三种不同失效程度对TVMS的影响。最后,在Solidworks中构建了故障斜齿轮副,并用有限元方法对其进行了仿真,验证了本文提出的不规则点蚀演化模型和计算方法的有效性。
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来源期刊
CiteScore
4.40
自引率
10.70%
发文量
234
审稿时长
4-8 weeks
期刊介绍: Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.
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