An approach for feature semantics recognition in geometric models
โ Scribed by Paolo Di Stefano; Francesco Bianconi; Luca Di Angelo
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 625 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0010-4485
No coin nor oath required. For personal study only.
โฆ Synopsis
This paper describes a method for the recognition of the semantics of parts (features) of a component from a pure geometric representation. It is suitable for verifying product life-cycle requirements from the early stages of the design process. The proposed method is appropriate to analyse B-rep geometric models, and it is not limited to models described by planar and cylindrical surfaces, but it can handle several types of face shapes. In this work the concept of semanteme is introduced. A semanteme represents the minimal element of engineering meaning that can be recognised in a geometric model. The semantemes recognised in a part of the model, which are potentially of engineering significance, are used to associate an engineering meaning to the part. This approach gives a wide flexibility to the proposed system, which is suitable to be used in different contexts of application, since it is possible to describe the reference context using the semanteme that the system can manage.
In the paper the implemented prototype system is briefly described. The prototype system takes advantage of neutral interfaces that allow geometrical and topological information to be retrieved from a commercial CAD system.
๐ SIMILAR VOLUMES
The paper presents a surface-based approach for geometric feature recognition for the purpose of automating the process planning of freeform surface machining. The proposed approach consists of the following four steps for recognition of the geometric features: conversion and preprocessing of the su
An OPS5 expert system has been developed, allowing the recognition of an arbitrary subpattern in a complex planar geometric figure under analysis. For this sake a syntactic representation for images is used by the expert system as a relational data base. The expert system looks for consistent mappin
In current feature-based parametric design systems, the reusability principle is not fully supported as it was expected. Unpredictability and ambiguity of models often happen during design modification within one system as well as among different systems. This reference deficiency significantly redu
This paper proposes an improved maximum model distance (IMMD) approach for HMM-based speech recognition systems based on our previous work [S. Kwong, Q.H. He, K.F. Man, K.S. Tang. A maximum model distance approach for HMM-based speech recognition, Pattern Recognition 31 (3) (1998) 219}229]. It de"ne