Multiscale features analysis of 3D surface topography based on mathematical morphology

Xiaojun Liu; Yi Huang; Kun Liu; Changlin Gui

doi:10.1117/12.717117

24 October 2006 Multiscale features analysis of 3D surface topography based on mathematical morphology

Xiaojun Liu, Yi Huang, Kun Liu, Changlin Gui

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63572E (2006) https://doi.org/10.1117/12.717117
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

In order to establish the relationship between the multi-scale features of 3D surface topography and its functional performances, a novel technique is presented for the multi-scale features characterization of 3D surface topography by greylevel morphological transform. By multi-scale morphological operations with structuring elements of different sizes, the structure features of the surface at different scales are extracted. Application of this technique to plateau honing surface has shown that multi-scale analysis based on the graylevel morphological transform is an effective method for providing texture components of different scales of 3D surface topography generated by multi-process manufacturing method. A new way to accurately determine the dividing point indicating the transition from fine plateau to deep groves is given. Based on the transition point, the surface bearing index and valley oil retention index are revised. The two revised parameters provide a more practical and exact means for characterizing the load carrying capacity and oil retention property of plateau honing surface.

Citation Download Citation

Xiaojun Liu, Yi Huang, Kun Liu, and Changlin Gui "Multiscale features analysis of 3D surface topography based on mathematical morphology", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63572E (24 October 2006); https://doi.org/10.1117/12.717117

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