A spalling evolution model for time-varying mesh stiffness evaluation and service life prediction of gears

Lu, Zhendan; Chen, Yunxia; Zu, Tianpei; Zhang, Wenbo

doi:10.1016/j.ymssp.2023.110227

Cited by 3 publications

(1 citation statement)

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“…Gear systems are typical transmission elements in power equipment, such as aircraft engines, wind turbines, and marine diesel engines, which operate under severe conditions of high speed, heavy load, and poor lubrication.Under these conditions, tooth spalling often occurs in the gear system, leading to a change in the dynamics and shortening the service life of the gear 1 , 2 . The time-varying mesh stiffness (TVMS), as the critical excitation source of the gear system, is a crucial factor in modelling gear dynamics.…”

Section: Introductionmentioning

confidence: 99%

A shape-independent analytical method for gear mesh stiffness with asymmetric spalling defects

Jin,

Zhang,

Chen

et al. 2024

Sci Rep

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Spalling, a common failure mechanism of gear systems, greatly affects the dynamics of gears operation, which is reflected in the time-varying mesh stiffness (TVMS). Current TVMS models often overestimate the asymmetric spalling phenomenon and may lead to inaccuracy in identifying and predicting the spalling failure. To address this problem, in this paper, a new stiffness, namely torsional stiffness, is introduced to quantify the effect of asymmetric spalling defects, and an equivalent stiffness calculation method for different asymmetric shapes is proposed. Based on this, a shape-independent TVMS model is constructed, which can realize the fast calculation of TVMS for spalling defects with different shapes at arbitrary asymmetric locations. Furthermore, a FEM-based validation method is developed by considering diverse loading states and improving the current result extraction method. Case studies are presented to illustrate the proposed model and to analyze the effects of different types of asymmetric spalling defects on gear dynamics. The FEM validation has shown that the proposed model has a good effectiveness.

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Section: Introductionmentioning

confidence: 99%