Quantifying Dynamic Oil Immersion in a Spiral Bevel Gear via Image Processing for Improved Churning Loss Prediction

This paper investigates the special phenomenon that the practical immersed depth of a spiral bevel gear as the driving gear under splash lubrication is significantly less than the static depth. To quantify the practical immersion depth, a computational fluid dynamics (CFD) approach integrated with image processing techniques is utilized to determine the dynamic immersion depth and the associated churning power loss. First, a theoretical method is developed to estimate the churning losses of the bevel gear by replacing the static immersion depth with the practical dynamic immersion depth. Subsequently, the CFD method, which incorporates the overset mesh technique and the volume-of-fluid (VOF) method, is employed to simulate the gear churning phenomenon. Meanwhile, the dynamic immersion depth is determined through image processing techniques that analyze the oil distribution characteristics in the splash-lubricated bevel gear. Finally, experimental results obtained from a dedicated lubrication test rig are favorably compared with the numerical results, confirming that the practical dynamic immersion depth is an accurate and effective parameter for calculating power losses.