A method for fast reconstruction of closed section workpiece surface using point clouds

Author:

Li Pei-Yao12,Song De-Ning12ORCID,Li Jing-Hua12,Zhou Lei12,Ma Jian-Wei3

Affiliation:

1. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China

2. Sanya Nanhai Innovation and Development Base of Harbin Engineering University, Sanya, China

3. Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, School of Mechanical Engineering, Dalian University of Technology, Dalian, China

Abstract

Parameterized reconstruction of workpiece surfaces is a critical step for advanced manufacturing applications, such as the solving of machining parameters, and the expression of workpiece in situ measurement. Generally, the point clouds model is easy to obtain and can be seen as the source model of the workpiece, and the B-spline surface is always taken as the ideal target parameterized model. Existing research focuses on reconstructing the single-valued surface, which can be projected onto a spatial plane without overlapping. However, the dual-valued surface, which overlaps at least twice, is also commonly encountered in industry, and has few investigations. Therefore, this paper proposes a fast reconstruction method based on reasonable segmentation and parameter domain mapping. In this approach, first, the dual-valued point clouds model is segmented into multiple single-valued point clouds models according to the sought edges in the optimal attitude. Then, the grid point coordinates of the single-valued point clouds model are calculated using the parametric-domain moving least squares method. Finally, the B-spline surface is generated by interpolating these grid points. The proposed algorithm is applied to single-bending closed-section workpieces such as the turbine blade to illustrate the effectiveness of this method. The contrast results with existing method demonstrate that the proposed approach can reconstruct the workpiece with multi-valued surfaces more quickly and more accurately, which is significant in advanced manufacturing.

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Applied Basic Research Plan of Liaoning Province

China Postdoctoral Science Foundation

Nature Science Foundation of Heilongjiang Province

Postdoctoral Science Foundation of Heilongjiang Province

Publisher

SAGE Publications

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