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Meshing position shift induced by eccentricity errors: Mechanisms and influences on stiffness, wear, and load sharing in planetary gears

  • Xingjian Dong
  • , Weiping Ouyang
  • , Shengyang Hu
  • , Zongde Fang
  • , Zhike Peng
  • , Shuai Gao
  • , Huayan Pu
  • , Jun Luo
  • Shanghai Jiao Tong University
  • Ltd
  • Anhui University of Science and Technology
  • Chongqing University

科研成果: 期刊稿件文章同行评审

摘要

Planetary gear systems inherently contain eccentricity errors that degrade dynamic performance and load sharing, causing distinct tooth wear patterns. To address this issue, an improved Loaded Tooth Contact Analysis (LTCA) model is developed to determine actual meshing positions through nonlinear iteration and predict the modulation effect of eccentricity on Time-Varying Mesh Stiffness (TVMS). A tooth wear prediction model accounting for micro-cycles of contact stress is also established. These components are integrated into a planetary gear dynamics model, forming a comprehensive “TVMS-dynamics-wear” framework for simulating full-lifecycle dynamic wear evolution. For healthy gears, early meshing increases average mesh stiffness by approximately 12% for external mesh pair and 15% for internal mesh pair, whereas delayed meshing reduces it by 9% and 3%, respectively. Throughout all wear stages, eccentricity errors continue exerting significant modulation on TVMS, leading to clearly differentiated wear patterns across tooth surfaces. Notably, under identical input shaft revolutions, the wear-induced TVMS fluctuation amplitude for internal mesh pairs is merely 3%–6% of that for external mesh pairs, indicating substantially less wear accumulation on internal meshing surfaces. Furthermore, as wear progresses, intensified force fluctuations cause progressive degradation of load sharing performance. Validated by experimental data, the integrated framework provides an effective numerical tool for investigating dynamic behavior and wear evolution in planetary gear systems with eccentricity errors, demonstrating good application potential for life cycle fault prognosis based on digital twins.

源语言英语
文章编号206685
期刊Wear
596
DOI
出版状态已出版 - 1 7月 2026

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