Measurement and Analysis Techniques for Surface Morphology of Engineering Ceramics Processing

The surface morphology is not only closely related to the machining methods and process parameters during the machining process, but also its texture characteristics largely determine the performance of components. In the electronics industry, the surface roughness of silicon wafers has an increasing impact on the thin film resistance and capacitance in integrated circuits, directly affecting the performance and yield of integrated circuit devices; In the national defense, military and aerospace industries, the surface morphology of optical lenses is even small

For a long time, the characterization of surface morphology has been two-dimensional, based on the contour lines obtained by scanning. However, with the deepening of surface analysis and the improvement of surface performance requirements, two-dimensional parameter characterization can no longer meet the requirements of the engineering community. Only three-dimensional detection and quantitative analysis can fully characterize the surface morphology. Currently, many international organizations, including ISO, are actively exploring three-dimensional characterization parameters.

Although three-dimensional morphology measurement is receiving increasing attention and has been continuously applied in the analysis of metal material cutting surface morphology, research on three-dimensional morphology measurement of ceramic grinding surfaces is still in its infancy. Many scholars still use two-dimensional contour parameters and evaluation methods when evaluating the quality of ceramic grinding surfaces. Although some scholars have also conducted research on the surface characteristics of ceramic grinding and started using three-dimensional morphology measurement for surface quality evaluation, most of them focus on the quality evaluation of a single sample, and there is still little comparative research on the three-dimensional morphology parameters of multi sample grinding surfaces.

The core of surface morphology evaluation lies in the undistorted extraction of feature signals and the quantitative evaluation of usage performance. In recent years, domestic and foreign scholars have done a lot of work in this area and proposed many separation and reconstruction methods. With the development of computing technology and mechatronics integration technology, various evaluation theories and methods have emerged, including least squares polynomial fitting, filtering, fractal, Motif, and functional parameter set methods, and significant progress has been made.

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