A feature-based method for tire pattern reverse modeling. (October 2018)

• Record Type: Journal Article
• Authors: Dong, Yude; Su, Fang; Sun, Genji; Liu, Yanchao; Zhang, Fangliang
• Is Part Of: Advances in engineering software. Volume 124(2018)
• Page Start: 73
• Page End: 89
• Publication Date: 2018-10
• Subjects: Point cloud -- Tire pattern -- Reverse engineering -- Semantic feature modeling; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2018.08.008
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: The point cloud data of tire tread are transformed into a point cloud mapping matrix to facilitate the extraction of the pattern features. The quality of pattern borders is improved by clustering similar tread patterns. The process of feature extraction and geometric element reconstruction are highly automated on CATIA platform by CAA. The pattern groove is constructed by feature modeling, thus the result model is editable. Abstract: In order to efficiently and effectively convert the tire point cloud to the 3D CAD model, a feature-based reverse modeling method reflecting the design intent of pattern structure is proposed in this paper. The concrete research contents are as follows. Firstly, the 3D scan line point cloud is transformed into the 2D point cloud mapping matrix based on range image. Secondly, the segmentation of the tread point cloud is completed with tread data and groove data separated. Thirdly, the top surface, bottom surface, and pattern boundary information is extracted from the segmented mapping matrix. And then the clustering of transversal patterns is carried out by calculating the similarity in order to repair pattern boundary and reduce human interactions. Finally, on the basis of the extracted parameters of pattern design feature, a semantic feature modeling method orienting at 3D tread pattern model is constructed. On the basis of the above theoretical study, a feature-based reverse modeling system for tire structure design is developed on the CATIA V5 platform by CAA. Test examples show the practicality of the system in tire pattern reverse modeling.