A Multivariate Local Descriptor Registration Method for Surface Topography Evaluation DOI Creative Commons
Chao Kong, Yuanping Xu, Zhuowei Li

и другие.

Applied Sciences, Год журнала: 2023, Номер 13(5), С. 3311 - 3311

Опубликована: Март 5, 2023

This paper illustrates a systematical surface topography measurement and evaluation method based on 3D optical system. Firstly, the point cloud data of workpiece are extracted by use structured light system, STEP file design model is converted into data. Secondly, local (LMPC) digital (DMPC) registered multivariate descriptor registration scheme proposed in this study. Thirdly, shapes from applied as reference to segment measuring cloud. Finally, an error analysis conducted specific functional surfaces. An experiment was analyse flatness, cylindricity roughness demonstrate effectiveness advantage method. The comparison results show that outperforms other methods.

Язык: Английский

Robust Isotropic Residual-Constrained VMD: A Novel Filter for Analyzing Engineering Surface Topography DOI Creative Commons
Qin Wen,

Nianqing Tang

IEEE Access, Год журнала: 2024, Номер 12, С. 29795 - 29811

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0
A Multivariate Local Descriptor Registration Method for Surface Topography Evaluation DOI Creative Commons
Chao Kong, Yuanping Xu, Zhuowei Li

и другие.

Applied Sciences, Год журнала: 2023, Номер 13(5), С. 3311 - 3311

Опубликована: Март 5, 2023

This paper illustrates a systematical surface topography measurement and evaluation method based on 3D optical system. Firstly, the point cloud data of workpiece are extracted by use structured light system, STEP file design model is converted into data. Secondly, local (LMPC) digital (DMPC) registered multivariate descriptor registration scheme proposed in this study. Thirdly, shapes from applied as reference to segment measuring cloud. Finally, an error analysis conducted specific functional surfaces. An experiment was analyse flatness, cylindricity roughness demonstrate effectiveness advantage method. The comparison results show that outperforms other methods.

Язык: Английский

Процитировано

1