SURFACE TOPOGRAPHY RECONSTRUCTION METHOD AND SYSTEM INTEGRATING MACHINE LEARNING AND SPATIAL FREQUENCY ANALYSIS

原文（中国語）

A surface topography reconstruction method integrating machine learning and spatial frequency analysis includes step 1: Using the analytical formula of the spatial frequency method to generate a large number of two-dimensional arrays that symbolize rough surfaces; step 2: by analyzing the height distribution and the frequency energy ratio of the generated surface, combined with the machine learning method, extracting the characteristic variable of the analytical formula; step 3: integrating the test or the simulation method to establish the relationship between the characteristic parameter and the surface property for performance prediction and surface reconstruction in a specific scenario. The surface topography reconstruction method can realize the surface topography characteristic extraction based on the spatial frequency analysis method, and reconstruct the rough surface suitable for the current-carrying performance prediction, thereby improving the practical significance of the surface reconstruction method in performance prediction.