Intelligent systems for volumetric feature recognition from CAD mesh models

Vaibhav J. Hase, Yogesh J. Bhalerao, Saurabh Verma, G. J. Vikhe Patil

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
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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.
Original languageEnglish
Pages (from-to)267-278
Number of pages12
JournalInternational Journal of Intelligent Enterprise
Issue number1/2/3
Publication statusPublished - 24 Jan 2020


  • CAD mesh model
  • CMM
  • Hybrid mesh segmentation
  • Volumetric feature recognition

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