Considerations in Positive to Negative Conversion for Machining Features Using Convex Decomposition

1993 ◽  
Author(s):  
Douglas L. Waco ◽  
Yong Se Kim
Keyword(s):  
Negative Component ◽  
Top Down ◽  
Machining Features ◽  
Convex Decomposition ◽  
Form Features ◽  
Common Parent ◽  
Parent Component ◽  
Form Feature ◽  
Negative Conversion

Abstract Form features intrinsic to the product shape can be recognized using a convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP). Since the form feature decomposition is compact and faithful to the product shape, it includes both positive and negative components. For machining applications, the positive components are converted into corresponding negative components to represent the removal volume. The positive to negative conversion is done in top-down manner by abstracting the positive components using halfspaces determined by the original faces and combining with the parent negative component. In this paper, we describe the considerations in handling interacting sibling positive components which have a common parent component.

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.

Conversions in Form Feature Recognition Using Convex Decomposition

1992 ◽  
Author(s):  
Yong Se Kim ◽  
Kenneth D. Roe
Keyword(s):  
Decomposition Method ◽  
Feature Recognition ◽  
Inductive Learning ◽  
The Other ◽  
New Combination ◽  
Convex Decomposition ◽  
Feature Information ◽  
Form Features ◽  
Primal And Dual ◽  
Form Feature

Abstract A convergent convex decomposition method called Alternating Sum of Volumes with Partitioning (ASVP) has been used to recognize volumetric form features intrinsic to the product shape. The recognition process is done by converting the ASVP decomposition into a form feature decomposition by successively applying combination operations on ASVP components. In this paper, we describe a method to generate new combination operations through inductive learning from conversion processes of primal and dual ASVP decompositions when one decomposition produces more desirable form feature information than the other.

1997 Status of the Form Feature Recognition Method Using Convex Decomposition

1997 ◽  
Author(s):  
Eric Wang ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Feature Representation ◽  
Boundary Representation ◽  
Current Status ◽  
Recognition Method ◽  
Convex Decomposition ◽  
Feature Representations ◽  
Negative Feature ◽  
Form Features ◽  
Form Feature

Abstract This paper describes the current status of our feature recognition method using a convex decomposition method called Alternating Sum of Volumes with Partitioning (ASVP). Volumetric form features are recognized from a part’s boundary representation by applying combination operations to the ASVP decomposition of the part to obtain a Form Feature Decomposition (FFD). The FFD can be post-processed to obtain application-specific feature representations; in particular, the conversion to the Negative Feature Decomposition (NFD), a machining feature representation, is described. Our domain of recognizable parts includes those having planar and cylindrical surfaces such that all cylindrical surfaces are bounded by straight edges and circular arcs, or are blending surfaces resulting from applying constant-radius blending to the part. We report the results of applying our method to the test parts for the 1997 Computers in Engineering Feature Panel Session.

Form Feature Recognition by Convex Decomposition

1991 ◽  
Author(s):  
Yong Se Kim
Keyword(s):  
Decomposition Method ◽  
Feature Recognition ◽  
Convex Hulls ◽  
Convex Decomposition ◽  
Geometric Objects ◽  
Volumetric Representation ◽  
Feature Information ◽  
Form Features ◽  
Form Feature

Abstract A convex decomposition method, called Alternating Sum of Volumes (ASV), uses convex hulls and set difference operations. ASV decomposition may not converge, which severely limits the domain of geometric objects that can be handled. By combining ASV decomposition and remedial partitioning for the non-convergence, we have proposed a convergent convex decomposition called Alternating Sum of Volumes with Partitioning (ASVP). In this article, we describe how ASVP decomposition is used for recognition of form features. ASVP decomposition can be viewed as a hierarchical volumetric representation of form features. Adjacency and interaction between form features are inherently represented in the decomposition in a hierarchical way. Several methods to enhance the feature information obtained by ASVP decomposition are also discussed.

Wavelet-Based Surface Analysis for Form Feature Extraction

2000 ◽  
Author(s):  
Lei Sun ◽  
Abir Qamhiyah
Keyword(s):  
Feature Extraction ◽  
Wavelet Transforms ◽  
Three Dimensional ◽  
Feature Representation ◽  
Cad Model ◽  
Vanishing Moments ◽  
Planar Surfaces ◽  
Solid Models ◽  
Form Features ◽  
Form Feature

Abstract A new procedure for extracting form features from solid models with non-planar surfaces is presented in this paper. In the procedure, a surface is selected as the unit for feature representation, i.e. “feature primitive.” Three-dimensional wavelet transforms are applied to code and classify surfaces in a CAD model. Form features are then extracted by clustering the coded surfaces. Two wavelet bases, Harr and Daubechies with different vanishing moments, have been implemented. An example is presented to demonstrate the proposed procedure.

Augmented Convex Decomposition Using Incremental Update for Recognition of Form Features

1996 ◽  
Author(s):  
Frédéric Parienté ◽  
Yong Se Kim
Keyword(s):  
Feature Recognition ◽  
Feature Representation ◽  
Boundary Representation ◽  
Central Feature ◽  
Decomposition Tree ◽  
Active Components ◽  
Convex Decomposition ◽  
Volumetric Representation ◽  
Incremental Update ◽  
Form Features

Abstract Alternating Sum of Volumes with Partitioning (ASVP) decomposition is a volumetric representation of a part obtained from its boundary representation that organizes faces of the part in an outside-in hierarchy. ASVP decomposition combines Alternating Sum of Volumes (ASV) decomposition, using convex hulls and set difference operations, and remedial partitioning, using cutting operations and concave edges. A Form Feature Decomposition (FFD) which can serve as a central feature representation for various applications is obtained from ASVP decomposition. The incremental update of convex decomposition is achieved by exploiting its hierarchical structure. For a connected incremental design change, the active components that only need to be updated are localized in a subtree of the decomposition tree called active subtree. Then, the new decomposition is obtained by only updating the active subtree in the old decomposition. In this paper, we present a new decomposition, called Augmented Alternating Sum of Volumes with Partitioning (AASVP) decomposition, that is incrementally constructed using ASV incremental update as a local operation on a decomposition tree. AASVP provides an improved feature recognition capability as it localizes the effect of the change in the decomposition tree, avoids excessive remedial partitioning and catches the designer’s intent in feature editing. AASVP differs from ASVP at the remedial-partitioning nodes by partitioning less. The current remedial partitioning method could be improved such that AASVP decomposition can be constructed directly from the solid model.

On the Viability of Developing CAD Data Exchange Standard for Form Features

2005 ◽  
Author(s):  
Nilesh S. Joshi ◽  
Jami J. Shah
Keyword(s):  
Data Exchange ◽  
Data Transfer ◽  
Design Feature ◽  
Feature Model ◽  
Finite Set ◽  
History Of ◽  
Standard Set ◽  
Form Features ◽  
Criteria For Evaluation ◽  
Form Feature

Form feature data exchange is divided into three types: CAD-to-CAD, CAD-to-Downstream applications and inter-downstream applications. Essential characteristics for CAD-to-CAD and CAD-to-Downstream types of feature data transfer are established flowed by a set of criteria for evaluation of a form feature exchange schema. Contemporary neutral feature data exchange schemas like AP 224, AP 203 and NRep are evaluated. It is concluded that none of them is fully equipped to do the job. AP 203 belongs to the CAD-to-CAD feature data exchange class. It exchanges only the final part geometry and the feature model is lost. AP 224 and NRep belong to the CAD-to-Downstream class. AP 224 attempts to enlist all features that can be manufactured using milling and turning processes. It limits the user to finite set of features. On the other hand, NRep permits the user to define his own features and does not provide a standard set. For a complete feature data transfer between two CAD applications, one needs to model the design intent of each design feature and transfer it with construction history of creation of the part model while for an efficient feature data transfer between CAD and downstream applications, the schema needs to standardize a set of most common features but also provide means for the user to define customized features with desired parameterization and attributes.

Effects of Geometric Form Features on Three-Dimensional Object Categorization

2005 ◽  
Vol 100 (3_suppl) ◽  
pp. 899-912 ◽  
Author(s):  
Shang H. Hsu ◽  
Wuefay Chang ◽  
Ming-Chuen Chuang
Keyword(s):  
Regression Analysis ◽  
Multidimensional Scaling ◽  
Three Dimensional ◽  
Object Categorization ◽  
Geometric Form ◽  
Female Undergraduate ◽  
Design Students ◽  
Form Features ◽  
Dimensional Object ◽  
Form Feature

The purpose was to investigate the effects of 3-D form features on the object-categorization process. 30 subjects [17 male and 13 female undergraduate industrial design students whose mean age was 20.7 yr. ( SD = 1.5)] were asked to classify 32 3-D prismatic images according to their similarity. Multidimensional scaling and cluster analyses indicated that the classification process was strongly related to the prisms' compounded features. The attention-weighting of each individual form feature was calculated by regression analysis which further indicated that each feature had a different effect on the categorizing process.

Sign in / Sign up

Export Citation Format

Share Document