3-D Interacting Manufacturing Feature Recognition

Soundar Rajan Tirupatikumara, Ching Yao Kao, Michael G. Gallagher, Rangachar Kasturi

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Automatic recognition of machining features such as slots, holes and pockets is one of the major tasks of CAD/CAM. This research proposes the super relation graph (SRG) method for extracting shape features. The nodes of the SRG represent the faces in depressions; the links represent either super-concavity or face-to-face relationships which are generated from a set of new definitions of relationships between two faces. Hypotheses are generated from a combination of graph-based and neural network approaches. These hypotheses are verified using computational geometry techniques. The SRG method is implemented in an object oriented paradigm and the results obtained are proved to be better than the ones generated from most of the prominent existing methods.

Original languageEnglish (US)
Pages (from-to)133-136
Number of pages4
JournalCIRP Annals - Manufacturing Technology
Volume43
Issue number1
DOIs
StatePublished - Jan 1 1994

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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