The contact performance of the tooth surface is a crucial factor affecting the operational lifespan of gears. There is a significant correlation between tooth surface topography and contact stress, as well as fatigue performance. To investigate the influence of different topography parameters on tooth surface contact stress, this paper performs analytical calculations on asperity contacts of rough tooth surfaces based on reconstruction modeling. Through efficient calculations, sufficient correlation analysis data is obtained. The neural network analysis method is used to measure the degree of influence of roughness parameters on tooth surface contact performance. Research on the correlation between micro-topography parameters and maximum contact stress on tooth surfaces, as well as regression analysis, is conducted. The results show that: (1) Considering rough surfaces, the tooth surface contact stress field exhibits two stress peaks in the near-surface layer and sub-surface layer, with a maximum Mises stress increase of up to 30 % compared to a smoother surface. (2) In the case of low roughness (Sa < 0.2 μm), the amplitude of the maximum Mises stress peak in the near-surface layer is close to that in the sub-surface layer. However, as the roughness amplitude increases, the amplitude of the near-surface stress peak increases sharply. (3) Ranking the roughness parameters based on their influence on contact stress, the main parameters characterizing contact performance are identified as Spk, Vmp, and Sq. The peak characteristics of the surface are the decisive factors affecting fatigue extremes, which are stronger than the traditional surface roughness parameter Sq. This paper establishes a direct correlation model between tooth surface topography parameters and contact stress, providing a foundation for simplifying stress calculations considering complex topographies and offering new insights for fatigue-resistant design of tooth surfaces.
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