Computational Analysis of Gear Meshing Excitations Considering Surface Roughness and Oil Film Effects

Accurately predicting gear meshing excitation is crucial for high-performance transmission fatigue design and noise optimization. To address the frequently overlooked topography-lubrication coupling, this paper presents a loaded tooth contact analysis (LTCA) model integrating ground surface features and oil film stiffness. Utilizing the finite element substructure method, the model combines a non-uniform sinusoidal function for surface waviness with the Dowson-Higginson film thickness formula. Results show that higher grinding wheel speeds enhance surface quality, bringing time-varying meshing stiffness (TVMS) and static transmission error (STE) levels closer to ideal smooth surfaces. Conversely, increased axial feed rates or fluctuation amplitudes deepen surface textures, causing stiffness attenuation and a significant STE amplitude surge. Additionally, higher lubricant viscosity, pressure-viscosity coefficients, or driving gear speeds thicken the oil film, reducing equivalent stiffness and elevating global transmission error. Crucially, the roughness-oil film coupling causes the most severe stiffness loss. This study offers a precise theoretical foundation for predicting precision gear system contact characteristics.