A new method for machining feature extracting of objects using 2D technical drawings

In this study, a new method called “3-Space” has been developed to obtain 3D models of prismatic machine parts using 2D technical drawings. This method uses 3 surfaces named Base, Top and Sweep Base for the determination of the objects. The edge colors have been given to the surfaces with meanings, and are used for the determination of the type and characteristics of the objects. 4 characteristics of the processing objects (namely external access direction, exit status, boundary geometry and the processing order of the features) have been determined. First, the object is considered a prismatic raw material, and the features to be processed on it are removed. Then the remaining object itself is created and thus a 3D view of the object is obtained.     

Reconstruction of 3D interacting solids of revolution from 2D orthographic views

3D CAD is replacing 2D CAD to improve efficiency of product design and manufacturing. Therefore, converting legacy 2D drawings into 3D solid models is required. CSG based approaches reconstruct solid models from orthographic views more efficiently than traditional B-rep based approaches. A major limitation of CSG based approaches has been the limited domain of objects that can be handled. This paper aims at extending the capabilities of CSG based approaches by proposing a hint-based recognition of interacting solids of revolution. This approach can handle interacting solids of revolution as well as isolated solids of revolution.     

Handling sectional views in volume-based approach to automatically construct 3D solid from 2D views

This paper presents an algorithm for solid model reconstruction from 2D sectional views based on volume-ba`sed approach. None of the existing work in automatic reconstruction from 2D orthographic views have addressed sectional views in detail. It is believed that the volume-based approach is better suited to handle different types of sectional views. The volume-based approach constructs the 3D solid by a boolean combination of elementary solids. The elementary solids are formed by sweep operation on loops identified in the input views. The only adjustment to be made for the presence of sectional views is in the identification of loops that would form the elemental solids. In the algorithm, the conventions of engineering drawing for sectional views, are used to identify the loops correctly. The algorithm is simple and intuitive in nature. Results have been obtained for full sections, offset sections and half sections. Future work will address other types of sectional views such as removed and revolved sections and broken-out sections.     

A single solution method for converting 2D assembly drawings to 3D part drawings

Although solid models play a central role in modern CAD systems, 2D CAD systems are still commonly used for designing products without complex curved faces. Therefore, an important task is to convert 2D drawings to solid models, and this is usually carried out manually even in present CAD systems. Many methods have been proposed to automatically convert orthographic part drawings of solid objects to solid models. Unfortunately, products are usually drawn as 2D assembly drawings, and therefore, these methods cannot be applied. A further problem is the difficult and time-consuming task of decomposing 2D assembly drawings into 2D part drawings. In previous work, the authors proposed a method to automatically decompose 2D assembly drawings into 3D part drawings, from which 2D part drawings can be easily generated. However, one problem with the proposed method was that the number of solutions could easily explode if the 2D assembly drawings became complex. Building on this work, here we describe a new method to automatically convert 2D assembly drawings to 3D part drawings, generating a unique solution for designers regardless of the complexity of the original 2D assembly drawings. The only requirement for the approach is that the assembly drawings consist of standard parts such as bars and plates. In 2D assembly drawings, the dimensions, part numbers and parts lists are usually drawn, and the proposed method utilizes these to obtain a unique solution.     

An interactive example-driven approach to graphics recognition in engineering drawings

An interactive example-driven approach to graphics recognition in engineering drawings is proposed. The scenario is that the user first interactively provides an example of a graphic object; the system instantly learns its graphical knowledge and uses the acquired knowledge to recognize the same type of graphic objects. The proposed approach represents the graphical knowledge of an object in terms of its structural components and their syntactical relationships. We summarize four types of geometric constraints for knowledge representation, based on which we develop an algorithm for knowledge acquisition. Another algorithm for graphics recognition using the acquired graphical knowledge is also proposed, which is actually a sequential examination of these constraints. In the algorithm, we first guess the next component’s attributes (e.g., size, position and orientation) by reasoning from an earlier found component and the constraint between them, and then search for this hypothetical component in the drawing. If all of the hypothetical components are found, a graphic object of this type is recognized. For improving the system’s recognition accuracy, we develop a user feedback scheme, which can update the graphical knowledge from both positive (missing) and negative (mis-recognized) examples provided by the user for subsequent recognition. Experiments have shown that our proposed approach is both efficient and effective for recognizing various types of graphic objects in engineering drawings. This paper is an extension of our papers published in ICDAR2003 and GREC2003.     

基于形体逼近的三维重建算法

该文提出一种新的由三视图重建三维实体的算法,能扩展自顶向下的三维重建算法的形体覆盖域,并在Auto-CAD平台上验证了算法的有效性。算法的主要步骤是首先用平扫-旋转-求交的实体运算法则构造出与所求实体形状相近的实体———第1参照体,再模拟人脑的识图过程:把第1参照体的三视图与初始三视图对比,根据两者之间的差别构造出差异体,再从第1参照体中逐一减去差异体,得到第2参照体、第3参照体......最后得到所求的实体。     

Recognition of simple and complex interacting non-orthogonal features

Feature recognition systems that deal with non-orthogonal features are seldom reported. This paper addresses this gap in the research by presenting a neural network-based feature recognition system to deal with non-orthogonal interacting features. The system accesses the B-rep data of a solid model, and searches for the feature volumes, using a cross-sectional layer method. The volumes are then transformed into 2D patterns of edges and vertices, using the conventions of ‘crosses and dots’ and ‘solid and dashed lines’. These feature patterns are later translated into input matrices for the recognition by a multilayer feedforward neural network.     

A structure-preserved local matching approach for face recognition

In this paper, a novel local matching method called structure-preserved projections (SPP) is proposed for face recognition. Unlike most existing local matching methods which neglect the interactions of different sub-pattern sets during feature extraction, i.e., they assume different sub-pattern sets are independent; SPP takes the holistic context of the face into account and can preserve the configural structure of each face image in subspace. Moreover, the intrinsic manifold structure of the sub-pattern sets can also be preserved in our method. With SPP, all sub-patterns partitioned from the original face images are trained to obtain a unified subspace, in which recognition can be performed. The efficiency of the proposed algorithm is demonstrated by extensive experiments on three standard face databases (Yale, Extended YaleB and PIE). Experimental results show that SPP outperforms other holistic and local matching methods.     

An approach to recognize interacting features from B-Rep CAD models of prismatic machined parts using a hybrid (graph and rule based) technique

This paper presents a new hybrid (graph + rule based) approach for recognizing the interacting features from B-Rep CAD models of prismatic machined parts. The developed algorithm considers variable topology features and handles both adjacent and volumetric feature interactions to provide a single interpretation for the latter. The input CAD part model in B-Rep format is preprocessed to create the adjacency graphs for faces and features of associated topological entities and compute their attributes. The developed FR system initially recognizes all varieties of the simple and stepped holes with flat and conical bottoms from the feature graphs. A new concept of Base Explicit Feature Graphs and No-base Explicit Feature Graphs has been proposed which essentially delineates between features having planar base face like pockets, blind slots, etc. and those without planar base faces like passages, 3D features, conical bottom features, etc. Based on the structure of the explicit feature graphs, geometric reasoning rules are formulated to recognize the interacting feature types. Extracted data has been post-processed to compute the feature attributes and their parent-child relationships which are written into a STEP like native feature file format. The FR system was extensively tested with several standard benchmark components and was found to be robust and consistent. The extracted feature file can be used for integration with various downstream applications like CAPP.     

Automatic 3D face recognition from depth and intensity Gabor features

As is well known, traditional 2D face recognition based on optical (intensity or color) images faces many challenges, such as illumination, expression, and pose variation. In fact, the human face generates not only 2D texture information but also 3D shape information. In this paper, we investigate what contributions depth and intensity information makes to face recognition when expression and pose variations are taken into account, and we propose a novel system for combining depth and intensity information to improve face recognition systems. In our system, local features described by Gabor wavelets are extracted from depth and intensity images, which are obtained from 3D data after fine alignment. Then a novel hierarchical selecting scheme embedded in linear discriminant analysis (LDA) and AdaBoost learning is proposed to select the most effective and most robust features and to construct a strong classifier. Experiments are performed on the CASIA 3D face database and the FRGC V2.0 database, two data sets with complex variations, including expressions, poses and long time lapses between two scans. Experimental results demonstrate the promising performance of the proposed method. In our system, all processes are performed automatically, thus providing a prototype of automatic face recognition combining depth and intensity information.     

Boundary analysis and geometric completion for recognition of interacting machining features

Features are the basic elements which transform CAD data into instructions necessary for automatic generation of manufacturing process plans. In this paper, a hybrid of graph-based and hint-based techniques is proposed to automatically extract interacting features from solid models. The graph-based hints generated by this approach are in geometrical and topological compliance with their corresponding features. They indicate whether the feature is 2.5D, floorless or 3D. To reduce the product model complexity while extracting features, a method to remove fillets existing in the boundary of a 2.5D feature is also proposed. Finally, three geometric completion algorithms, namely, Base-Completion, Profile-Completion and 3D-volume generation algorithms are proposed to generate feature volumes. The base-completion and profile-completion algorithms generate maximal volumes for 2.5D features. The 3D volume generation algorithm extracts 3D portions of the part.     

An approach to identify design and manufacturing features from a data exchanged part model

Due to the large variety of CAD systems in the market, data exchange between different CAD systems is indispensable. Currently, data exchange standards such as STEP and IGES, etc. provide a unique approach for interfacing among different CAD platforms. Once the feature-based CAD model created in one CAD system is input into another via data exchange standards, many of the original features and the feature-related information may not exist any longer. The identification of the design features and their further decomposition into machining features for the downstream activities from a data exchanged part model is a bottleneck in integrated product and process design and development. In this paper, the feature panorama is succinctly articulated from the viewpoint of product design and manufacturing. To facilitate feature identification and extraction, a multiple-level feature taxonomy and hierarchy is proposed based on the characteristics of part geometry and topology entities. The relationships between the features and their geometric entities are established. A litany of algorithms for the identification of design and machining features are proposed. Besides, how to recognize the intersecting features or compound features based on the featureless chunks of geometry entities is critical and the issue is addressed in the paper. A multi-level compound feature representation and recognition approach are presented. Finally, case studies are used to illustrate the validity of the approach and algorithms proposed for the identification of the features from CAD part models in neutral format.     

A surface based approach to recognition of geometric features for quality freeform surface machining

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 surface geometry data, subdivision of NURBS surface, reconstruction of surface orientation areas, and recognition of geometric features. The proposed scheme assumes that the input geometry data form is based on an IGES CAD model and the surface model can be represented in the form of trimmed NURBS surfaces. The connectivity relations of the product surfaces are analyzed and each surface is subdivided into orientation regions based on the surface normal vector over a certain point density grid, and then all the connected regions with the same orientation type are grouped into surface orientation areas. After that, the geometric feature will be recognized through the analysis of area connectivity and relationship. The paper describes the developed algorithms on surface orientation region subdivision, surface orientation area reconstruction, and geometric feature recognition. The verified feasibility study of the developed method is also presented.     

From Raster to Vectors: Extracting Visual Information from Line Drawings

Vectorisation of raster line images is a relatively mature subject in the document analysis and recognition field, but it is far from being perfect as yet. We survey the methods and algorithms developed to-date for the vectorisation of document images, and classify them into six categories: Hough transform-based, thinning-based, contour-based, run-graph-based, mesh-pattern-based, and sparse-pixel-based. The purpose of the survey is to provide researchers with a comprehensive overview of this technique, to enable a judicious decision while selecting a vectorisation algorithm for a system under development or a newly developed vectorisation algorithm. Received: 10 November 1998?Received in revised form: 7 January 1999?Accepted: 7 January 1999     

A graph-based expert system approach to geometric feature recognition

Geometric feature recognition is a crucial task in the development of concurrent engineering software. This paper presents a new methodology for geometric feature recognition which combines the advantages of face-edge adjacency graphs and expert systems. The methodology uses several new concepts such as enhanced winged edge data structure (EWEDS) and multi-attributed adjacency graphs (MAAG). The object model is presented as a set of facts. The rules for the recognition of each feature are derived from the corresponding feature-MAAG. This simplifies the process of writing the rules while enabling the inclusion of new features into the rule base as they are encountered.     

A feature-based approach to injection mould cooling system design

Most existing work on the design of cooling systems of plastic injection moulds has been focused on the detailed analysis or the optimization of the cooling system. However, before a cooling system can be analysed or optimized, an initial design has to be developed. We explore a new design synthesis approach to solve this initial design problem. A plastic part with a complex shape is decomposed into simpler shape features. The cooling systems of the individual features are first obtained, they are then combined to form the cooling system of the entire part. Decomposing a complex shape into shape features is a feature recognition problem. A new algorithm for the recognition of features specific to cooling system design is developed. Design examples generated by the design synthesis process are analysed by C-Mold to verify the feasibility of the approach.     

A feasible approach to the integration of CAD and CAPP

Although current CAD systems are declared to be feature-based, in fact, the so-called feature is just a modeling macro or menu name such as Protrusion, Revolution, Cutout, Block, etc., instead of a design feature or manufacturing feature in accordance with engineering practice. Consequently, product model data insufficiency and incompatibility between varieties of application systems are still the major barriers to system integration, especially the integration of design and process planning. This paper proposes a practical solution for a bi-directional integration of CAD and CAPP on the platform of commercial CAD systems. The key techniques such as feature recognition and conversion, feature parameter and constraint extraction, feature tree reconstruction, technical information processing, process planning, automatic process drawing marking and 3D material stock CAD model generating are discussed. And the extracted features and their related technical information and knowledge are encapsulated together with the geometry-oriented CAD model to form an integrated product information model to facilitate effective integration with the downstream activities. The integrated CAD/CAPP system is implemented on a commercial CAD package, UGS/SolidEdge. A case study and industry implementation illustrate the feasibility of the approach proposed.