Simulating the worn surface in a wear process

The mathematical expression of surface geometry and topography is the first step towards modeling the performance of tribological elements with rough surfaces. The recent trend of tribological simulations, as well as failure prediction, demands the description of surface changes in a wear process. Reported in this paper is a method developed to simulate surfaces in a wear process through connecting wear tests with statistical and artificial-intelligent analyses. The simulation method consists of four components: (1) wear tests for the pivot information of surface variation in wear, (2) statistical analyses for surface feature extraction, (3) artificial neural network (ANN) processing for test result generalization, and (4) surface synthesis for worn surface regeneration. Selected wear tests are performed to lay the ground for the simulation. The simulation method is used to generate the worn surfaces, based on the original statistical parameters and the prediction of their variations due to wear, for a group of engineered surfaces of the same nature and subjected to the same wear process.