Prediction of Surface Wear of Involute Gears Based on a Modified Fractal Method

Abstract

A new wear prediction method of tooth surfaces of involute gears based on a real tooth surface model and a modified fractal method is developed. The real tooth surface model of an involute gear pair is introduced, and microgeometry feature detection of tooth surfaces is achieved by monitoring variations of normal vectors of each discrete data point of the real tooth surface model. To predict wear progression of tooth surfaces of a gear pair, an abrasive wear analysis model and the modified fractal method are used to analyze contact performance and its changes with accumulation of surface wear. The abrasive wear analysis model can analyze wear depths of gear tooth surfaces with sliding distances, local contact pressure, and directions of wear progression based on Archard's model. The modified fractal method is proposed to calculate instantaneous contact stiffness and estimate elastic and plastic deformation regions based on an asperity contact model. Microgeometry features of tooth surface asperities can be described as the basis of an asperity contact model and allow tooth contact analysis of real tooth surface models with their local microgeometry feature changes due to plastic deformations. Feasibility and effectiveness of this wear prediction method were verified by comparing predicted results of gear surface wear progression with gear wear test results.