A Dempster–Shafer approach for recognizing machine features from CAD models

✍ Scribed by Qiang Ji; Michael M. Marefat

• Publisher: Elsevier Science
• Year: 2003
• Tongue: English
• Weight: 201 KB
• Volume: 36
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(02)00260-1

✦ Synopsis

This paper introduces an evidential reasoning-based approach for recognizing and extracting manufacturing features from solid model description of objects. A major di culty faced by previously proposed methods for feature extraction has been the interaction between features due to non-uniqueness and ambiguousness in feature representation. To overcome this di culty, we introduce a Dempster-Shafer approach for generating and combining geometric and topologic evidences to identify and extract interacting features.

The main contributions of this research include introducing di erent classes of evidences based on the geometric and topologic relationships at di erent abstraction levels for e ective evidential reasoning and developing the principle of association to overcome the mutual exclusiveness assumption of the Dempster-Shafer theory. Experiments demonstrate the e ectiveness of the proposed approach in extracting interacting machine features.