Intelligent Systems for Volumetric Feature Recognition from CAD Mesh Models

Abstract

This paper presents an intelligent technique to recognize the volumetric features from CAD mesh models based on hybrid mesh segmentation. The hybrid approach is an intelligent blending of facet-based, vertex based, rulebased, and machine learning based techniques. Comparing with existing stateof-the-art approaches, the proposed approach does not depend on attributes like curvature, minimum feature dimension, number of clusters, number of cutting planes, the orientation of model and thickness of the slice to extract volumetric features. The intelligent threshold prediction makes hybrid mesh segmentation automatic. The proposed technique automatically extracts volumetric features like blends and intersecting holes along with their geometric parameters. The proposed approach has been extensively tested on various benchmark test cases. The proposed approach outperforms the existing techniques favorably and found to be robust and consistent with coverage of more than 95% in addressing volumetric features

Quantitative Performance Analysis of Hybrid Mesh Segmentation

“…We evaluate using the coverage percentage, a number of primitives, and the distance error. As noted by [39], the HMS algorithm yields better results than RANSAC [5] and Attene et.al. [4].…”