Abstract

Residual stress and hardness gradient significantly affect the contact fatigue failure process of rough tooth surfaces, and the meticulous design of their characteristic parameters can help improve the fatigue resistance of gears. In this paper, an efficient computational method for rough tooth surface contact is established based on the reconstruction modeling of asperities and mixed lubrication analysis. By comprehensively considering the effects of residual stress and hardness gradient, the Dangvan multiaxial fatigue criterion is adopted to predict and analyze the contact fatigue life of the gear surface. The correlation between the surface residual stress, maximum residual stress depth, surface hardness, and effective hardening layer depth, among other characteristic parameters, and the contact fatigue performance of tooth surfaces is established. The results show that: (1) Increasing the magnitude of surface residual compressive stress and surface hardness can significantly reduce the risk of fatigue failure in the near-surface layer of the gear. To achieve the same fatigue performance, there is a linear negative correlation between the design values of the two parameters. (2) Affected by the double stress peaks in the rough tooth surface stress field, the maximum residual stress depth significantly affects the depth at which the highest failure risk occurs. With changes in roughness, the optimal design value of the maximum residual compressive stress depth changes from about 0.5 times the Hertzian contact half-width depth in the subsurface layer (Sa < 0.2 μm) to about 15 μm in the near-surface layer (Sa > 0.4 μm). (3) Considering both process cost and gear surface fatigue resistance, the design threshold for the effective hardening layer depth should be greater than the Hertzian contact half-width. This paper establishes a composite correlation between the meticulous characteristic parameters of residual stress, hardness gradient, and the contact fatigue performance of tooth surfaces, providing theoretical support for optimal design of tooth surface anti-fatigue performance.

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