Research on Shape Feature Recognition of Boundary Representation CAD Model

2017 ◽  
Vol 14 (1) ◽  
pp. 477-484
Author(s):  
Jihua Wang
Keyword(s):  
Feature Recognition ◽  
Boundary Representation ◽  
Surface Boundary ◽  
Cad Model ◽  
Shape Feature ◽  
Product Model ◽  
Data Files ◽  
Visual Mechanism ◽  
Human Visual Mechanism ◽  
Visual Shape

B-Rep (Boundary Representation) CAD model is being widely used in representation of industrial product, so its feature recognition has acquired widespread research interests in computer vision and 3D model retrieval fields. We present one approach of feature recognition based on the idea of human visual mechanism. Surfaces as the visual shape features, and solids as well as shells as the topological relations, were extracted from the neutral STEP (Standard for Exchange of Product Model Data) files of B-Rep model. Towards three surface types of NURBS, analytical and poly loop, the properties of surface boundary and region are established based on curvature and other geometric index. So B-Rep CAD model is characterized as the hierarchical tree with solid layer, shell layer and surface layer for object recognition and retrieval, and the corresponding experiments verified the effectiveness of the method of shape feature recognition.

scholarly journals Research on Shape Feature Recognition of B-Rep Model Based on Wavelet Transform

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Jihua Wang
Keyword(s):  
Wavelet Transform ◽  
Feature Recognition ◽  
Feature Vector ◽  
3D Structure ◽  
Data File ◽  
Boundary Representation ◽  
Surface Boundary ◽  
Shape Feature ◽  
Product Model ◽  
Model Based

B-Rep (Boundary Representation) CAD model is widely used in the representation of manufactured product in computer, and it is a kind of real 3D structure with invisible part relative to 2.5D mesh model, so the shape feature recognition of B-Rep model is worth of much studying. We present one approach of shape feature recognition of B-Rep model based on the wavelet transform of surface boundary and region; it is inspired by the neuropsychology view that surface is the key visual features and by the systematology method that an object is recognized by decomposing and grouping its similar parts. Surface elements of B-Rep model are extracted from the neutral STEP (Standard for Exchange of Product Model Data) file; the curvatures of surface boundary and region were decomposed by wavelet transform, and then the coefficient statistics of same scale were as the surface feature vector. Similar surfaces of B-Rep model were clustered as a bin with the sum of perimeters and the mean vector, and all bins constituting a histogram are finally as the feature vector of B-Rep model. Thus B-Rep models are compared and retrieved using the EMD (Earth Mover’s Distance) of histogram. Our approach was evaluated by retrieval experiment with NDR (National Design Reservoir), and the result indicated its highly competent performance.

Geometric Reasoning for the Coding of CAD Models

1995 ◽  
Author(s):  
A. Z. Qamhiyah ◽  
B. Benhabib ◽  
R. D. Venter
Keyword(s):  
Computer Aided Design ◽  
Feature Recognition ◽  
Effective Means ◽  
Boundary Representation ◽  
Cad Model ◽  
Cad System ◽  
Cad Models ◽  
Form Features ◽  
Feature Based Design ◽  
Design Retrieval

Abstract Many of today’s concurrent product-development cycles depend on the utilization of intelligent Computer-Aided Design (CAD) systems. Thus, it would be essential to provide CAD users with effective means for interacting with the CAD system and its database. This paper addresses the development of a boundary-based coding procedure for CAD models. Coding the geometric and processing characteristics of objects, based on their CAD model representation, has been long recognized as an effective approach that allows convenient design retrieval on the one hand and process-planning automation on the other. Our work is based on the assumption that form features are recognizable and extractable from the CAD model by current feature-recognition, feature extraction and feature-based-design approaches. The coding procedure is applicable to the boundary representation of the object and its extracted form features.

MMCs and PPCs As Constructs of Curvature Regions for Form Feature Determination

1997 ◽  
Author(s):  
Ratnakar Sonthi ◽  
Rajit Gadh
Keyword(s):  
Feature Recognition ◽  
Geometric Model ◽  
Boundary Representation ◽  
Solid Model ◽  
Cad Model ◽  
Solid Models ◽  
Feature Information ◽  
Primitive Shape ◽  
Region Representation ◽  
Form Feature

Abstract Shape feature information about a part is required to analyze the part for downstream issues such as manufacturability and assemblability. One method of obtaining the feature information is feature recognition from the geometric model. This paper presents an approach called Curvature Region (CR) approach for feature determination in solid models. The CR-approach categorizes features into two primitive shape classes: protrusions and depressions. In the first step, these primitive shape classes are recognized from the solid model. In the next step, the primitive shape classes are analyzed using rules to obtain features. Primitive features are found by first converting the boundary representation (B-Rep) of the CAD model to a higher level of representation called Curvature Region Representation (CR-Rep). Curvature Regions are then grouped together to form Minus-Minus Centers (MMCs) and Plus-Plus Centers (PPCs). Primitive shapes are then defined in terms of these centers.

scholarly journals Feature Recognition for Manufacturability Analysis

1994 ◽  
Author(s):  
William C. Regli ◽  
Satyandra K. Gupta ◽  
Dana S. Nau
Keyword(s):  
Time Complexity ◽  
Material Removal ◽  
Feature Recognition ◽  
Solid Modeling ◽  
Cad Model ◽  
Worst Case ◽  
Machining Features ◽  
Automated Recognition ◽  
Wide Range ◽  
Complete Set

Abstract While automated recognition of features has been attempted for a wide range of applications, no single existing approach possesses the functionality required to perform manufacturability analysis. In this paper, we present a methodology for taking a CAD model of a part and extracting a set of machinable features that contains the complete set of alternative interpretations of the part as collections of MRSEVs (Material Removal Shape Element Volumes, a STEP-based library of machining features). The approach handles a variety of features including those describing holes, pockets, slots, and chamfering and filleting operations. In addition, the approach considers accessibility constraints for these features, has an worst-case algorithmic time complexity quadratic in the number of solid modeling operations, and modifies features recognized to account for available tooling and produce more realistic volumes for manufacturability analysis.

Handling Blending Features in Form Feature Recognition Using Convex Decomposition

1994 ◽  
Author(s):  
Sreekumar Menon ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Boundary Representation ◽  
Recognition Method ◽  
Geometric Information ◽  
Polyhedral Model ◽  
Curved Boundary ◽  
Convex Decomposition ◽  
Geometric Objects ◽  
Form Features ◽  
Form Feature

Abstract Form features intrinsic to the product shape can be recognized using a convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP). However, the domain of geometric objects to which ASVP decomposition can be applied had been limited to polyhedral solids due to the difficulty of convex hull construction for solids with curved boundary faces. We develop an approach to extend the geometric domain to solids having cylindrical and blending features. Blending surfaces are identified and removed from the boundary representation of the solid, and a polyhedral model of the unblended solid is generated while storing the cylindrical geometric information. From the ASVP decomposition of the polyhedral model, polyhedral form features are recognized. Form feature decomposition of the original solid is then obtained by reattaching the stored blending and cylindrical information to the form feature components of its polyhedral model. In this way, a larger domain of solids can be covered by the feature recognition method using ASVP decomposition. In this paper, handling of blending features in this approach is described.

Information Processing in Visual System - Optical Illusion and Visual Mechanism

2001 ◽  
Vol 13 (6) ◽  
pp. 569-574
Author(s):  
Masanori Idesawa ◽  
Keyword(s):  
Information Processing ◽  
Visual System ◽  
Visual Function ◽  
External World ◽  
Automated System ◽  
Human Beings ◽  
Optical Illusion ◽  
Optical Illusions ◽  
Visual Mechanism ◽  
Human Visual Mechanism

Human beings obtain big amount of information from the external world through their visual system. Automated system such as robot must provide the visual functions for their flexible operations in 3-D circumstances. In order to realize the visual function artificially, we would be better to learn from the human visual mechanism. Optical illusions would be a pure reflection of the human visual mechanism; they can be used for investigating human visual mechanism. New types of optical illusion with binocular viewing are introduced and investigated.

A Feature Recognition Approach with Fuzzy ART Neural Network

2011 ◽  
Vol 279 ◽  
pp. 406-411
Author(s):  
Cong Lu ◽  
Jun Zha
Keyword(s):  
Neural Network ◽  
Feature Recognition ◽  
Boundary Representation ◽  
Solid Model ◽  
Fuzzy Art ◽  
Fast Learning ◽  
Key Technologies ◽  
Learning Modes ◽  
Slow Learning

This paper proposes a feature recognition approach from a boundary representation solid model with Fuzzy ART neural network. To recognize the feature efficiently, some key technologies in Fuzzy ART neural network are used. The influence of the vigilance parameter on feature recognition is studied, and two learning modes, fast learning and slow learning are adopted and compared in feature recognition. Finally, a case study is given to verify the proposed approach.

Sign in / Sign up

Export Citation Format

Share Document