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Hase, Vaibhav J., Bhalerao, Yogesh J. 
ORCID: https://orcid.org/0000-0002-0743-8633, Verma, Saurabh and Patil, G. J. Vikhe
(2020)
Intelligent systems for volumetric feature recognition from CAD mesh models.
International Journal of Intelligent Enterprise, 7 (1/2/3).
pp. 267-278.
ISSN 1745-3232
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Abstract
This paper presents an intelligent technique to recognise the volumetric features from CAD mesh models based on hybrid mesh segmentation. The hybrid approach is an intelligent blending of facet-based, vertex based, rule-based, and artificial neural network (ANN)-based techniques. Comparing with existing state-of-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. ANN-based 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 favourably and found to be robust and consistent with coverage of more than 95% in addressing volumetric features.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | cad mesh model,cmm,hybrid mesh segmentation,volumetric feature recognition,business and international management,strategy and management,management of technology and innovation ,/dk/atira/pure/subjectarea/asjc/1400/1403 |
| Faculty \ School: | Faculty of Science > School of Engineering |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 07 Feb 2020 05:08 |
| Last Modified: | 22 Oct 2022 05:47 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/73984 |
| DOI: | 10.1504/IJIE.2020.104661 |
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