MACHINING FEATURE RECOGNITION USING AN EXTENDED GRAPH THEORY

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RAHMANI K.; AREZOU BEHROUZ

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Paper Information

Journal: AMIRKABIR Year:2007 | Volume:17 | Issue:65-B Page(s): 61-73

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Information Journal Paper

Title

MACHINING FEATURE RECOGNITION USING AN EXTENDED GRAPH THEORY

Author(s)

RAHMANI K. | AREZOU BEHROUZ | Issue Writer Certificate

Keywords

CADQ3

CAMQ3

CAPPQ3

FEATURE RECOGNITIONQ3

GRAPH THEORYQ3

Abstract

Manufacturing FEATURE RECOGNITION is a basic component for systems that automatically generate manufacturing processes. When compared to the set of low level entities existing in a component's CAD model, features are a set of higher level entities that model the correspondence between design information and manufacturing activities. Graph-based methods, which use the part adjacency graph to recognize features, are among the most common techniques in the existing FEATURE RECOGNITION literature. In this paper, some techniques are proposed which significantly improve the performance of traditional graph-based algorithms. The approach is more general and efficient than common graph-based approaches dealing with the problem of feature interactions. The scope of the graph-based approaches is also extended in this paper to include curved and 3D features in addition to polyhedral features, where most of the existing graph-based algorithms have focused only on the polyhedral objects.

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APA: Copy

RAHMANI, K., & AREZOU, BEHROUZ. (2007). MACHINING FEATURE RECOGNITION USING AN EXTENDED GRAPH THEORY. AMIRKABIR, 17(65-B), 61-73. SID. https://sid.ir/paper/905/en

Vancouver: Copy

RAHMANI K., AREZOU BEHROUZ. MACHINING FEATURE RECOGNITION USING AN EXTENDED GRAPH THEORY. AMIRKABIR[Internet]. 2007;17(65-B):61-73. Available from: https://sid.ir/paper/905/en

IEEE: Copy

K. RAHMANI, and BEHROUZ AREZOU, “MACHINING FEATURE RECOGNITION USING AN EXTENDED GRAPH THEORY,” AMIRKABIR, vol. 17, no. 65-B, pp. 61–73, 2007, [Online]. Available: https://sid.ir/paper/905/en

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