Doug E. R. Clark

Method for finding holes and pockets that connect multiple faces in 2 1/2D objects

Abstract Given a boundary representation, the problem of identifying sets of faces that bound holes and pockets in 2 1/2D objects is relatively trivial when they emanate from a single face, because the edges of the depression form an inner loop of convex edges. There are, however, many components in which a hole or pocket is present, and yet defines no inner loop on any face; in other words, it has a nonunique entrance face. The paper describes an algorithm, based on the manipulation of a face—edge graph, for identifying sets of faces in a 2 1/2D object that bound holes or pockets with unique or nonunique entrance faces. The algorithm also determines the perimeter of the projected area enclosed by each hole or pocket in a specific direction. This information is of direct use in the manufacture of the component.

Delta-volume decomposition for multi-sided components

Abstract The subdivision of the removal, or delta-volume, of a machined component into meaningful volumes suitable for efficient machining is at present a complex and time-consuming task. An algorithm is presented for recognizing CNC machining volumes from 3D boundary representation solid models. The 2.5D volumes identified are associated with generic depressions and protrusions. The novelty of the algorithm lies in the fact that its success does not depend upon a pre-defined library of features and that it guarantees the accessibility of the volumes found.

The Heriot-Watt FeatureFinder: CIE97 results

This paper describes the functionality of a Feature Recognition system, known as FeatureFinder. The systems algorithm has been developed from a graph-based approach to feature recognition and is now capable of identifying a variety of features on a wide range of machined components. The system has been designed to be used within a solids machining package and identifies features from a specified tool approach direction. The paper details the result of applying the algorithm to the CIE97 test pieces. Features are identified on all of the components and the paper concludes with a brief description of on-going work designed to extend the range of components FeatureFinders algorithm can analyse.

Efficient face-based feature recognition

Previous work of the authorsshowed how multiply connected protrusions and depressions could be identified through the detection of bounding face-cycles. This method, as previously described, had two weaknesses. Fust, it assumed that the 2~D axis of the object was given by the human user. Second, identification of the face-cycles, using standardalgorithms from graph theory, carried a high combinatorial overhead. This paper reportsfurtherwork which overcomes both of these problems, and illustrates a new cycle finding search strategy which has been implemented using the ACIS modeler. Keywom3:Feature Recognition, Aspect V6ctor,FaceEdge Oraph,Search Algorithm, Face cycles.

A feature recognition algorithm for multiply connected depressions and protrusions in 2 1/2 D objects

The authors discuss how the edge-based structuring of most commercial modelers has subtly influenced the approach taken in the majority of B-rep featurerecognition algorithms. Many of the problems that edge-based recognition methods handle badly, such as feature interaction and ambiguity, are shown to be resolved elegantly by adopting face-based recognition techniques. An algorithm is described which identifies multiply connected holes, pockets and islands in 2 ~ D i objects. The method is inspired by the face-e ge representation [A]l and the aspect graphs [G2] of computer vision research. These two ideas have been combined to produce a recognition algorithm that is both conceptually simple and robust.

A surface partitioning spectrum (SPS) for retrieval and indexing of 3D CAD models

Manual indexing of large databases of geometric information is costly and often impracticable. Because of this research into retrieval and indexing schemes has focused on the development of various 3D to 2D mappings that characterise a shape as a histogram with a small number of parameters. Many methods of generating such 2D signatures (i.e. histograms) have been proposed, generally based on geometric measures of say curvature or distance. However these geometric signatures lack information about topology and tend to become indistinct as the complexity of the shape increases. This work describes a new method for characterising both the geometry and topology of shapes in a single 2D graph, the surface partitioning spectrum (SPS). We evaluate the effectiveness of using the SPS with a neural network to assess the similarity of shapes within a test set.

A feature recognition algorithm for NC-machining

Previous work of the authors (Corney, 1993) has been extended to allow the recognition of closed depression and protrusion features on components containing cylindrical faces. The aim is to automate the creation of volumes which need to be cleared from a stock body in order to manufacture a component. The original algorithm was inefficient because geometric interrogations on complex components were repeated and a large amount of backtracking was required. In the new approach the interrogations are performed prior to the search algorithm. The recognition algorithm will eventually be extended to detect open features and to handle multi-sided components. The theory in this paper pertains only to single-sided, 2½-dimensional components.

Interpreting Three-Dimensional Shape Distributions

Abstract Effective content-based shape retrieval systems would allow engineers to search databases of three-dimensional computer-aided design (CAD) models for objects with specific geometries or features. Much of the academic work in this area has focused on the development of indexing schemes based on different types of three-dimensional to two-dimensional ‘shape functions’. Ideally, the shape function used to generate a distribution should be easy to compute and permit the discrimination of both large and small features. The work reported in this paper describes the properties of three new shape distributions based on computationally simple shape functions. The first shape function calculates the arithmetic difference between distributions derived (using the original D2 distance shape function) from both a three-dimensional model and its convex hull. The second shape function is obtained by sampling the angle between random pairs of facets on the object. The third shape function uses the surface orientation to filter the results of a distance distribution. The results reported in this paper suggest that these novel shape functions improve significantly the ability of shape distributions to discriminate between complex engineering parts.

Laminae-based feature recognition

Motivated by the needs of mould and die manufacturers, this paper presents a novel approach to recognizing shape features on geometric models composed of both simple and complex ruled surfaces. The algorithm described uses a network of adjacent 2D-laminae (i.e., bounded surfaces) derived from a components CAD model to both locate and create generic protrusion and depression feature volumes. The approach also enables the automatic generation of alternative feature descriptions and requires no predefined feature libraries.

Shapesifter: A retrieval system for databases of 3D engineering data

Large amounts of 3D data are being generated daily from increasingly diverse sources. In applications ranging from medical imaging and archival scanning of archaeological artifacts through to engineering and design, valuable geometric information is being recorded and stored. The size of these 3D databases make manual indexing time consuming, ineffective and often simply impracticable. Because of this, researchers have started to develop tools for automatically searching and organising these digital libraries of shape information. The most widespread and valuable form of 3D data are the design models created by commercial manufacturing companies. Engineering companies commonly have tens of thousands of 3D Computer‐Aided Design models stored on their computer systems. These models are used to communicate the exact shape and dimensions of components to both customers and subcontracting manufacturers. Consequently these models are of great value and importance to the companies. Currently 3D models (like engineering drawings) are indexed by alpha‐numeric ‘part numbers’ with a format unique to each company. Although this system of indexing works well in the context of ongoing maintenance and development of individual parts, it offers little scope for ‘data mining’ (i.e. exploration) of a companys inventory of designs. This paper describes an online system which allows collections of 3D models to be searched for components geometrically similar to a user‐defined target model. It is anticipated that such a system will encourage much