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Annotation and Retrieval System of CAD Models Based on Functional Semantics

Chinese Journal of Mechanical Engineering 2014年第6期27卷 1112-1124页

作者： WANG Zhansong TIAN Ling DUAN Wenrui State Key Laboratory of Tribology & Institute of Manufacturing Engineering Department of Mechanical EngineeringTsinghua University Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control Tsinghua University

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs（AAG） is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System（FSMARS）, is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

关键词： conceptual design functional semantics attributed adjacency graph CAD Model Repository multi-function extended retrieval

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An Intelligent Identification Approach of Assembly Interface for CAD Models

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 859-878页

作者： Yigang Wang Hong Li Wanbin Pan Weijuan Cao Jie Miao Xiaofei Ai Enya Shen School of Media and Design Hangzhou Dianzi UniversityHangzhou310001China School of Software Tsinghua UniversityBeijing100084China

Kinematic semantics is often an important content of a CAD model(it refers to a single part/solid model in this work)in many applications,but it is usually not the belonging of the model,especially for the one retrieved from a common ***,the effective and automatic method to reconstruct the above information for a CAD model is still *** address this issue,this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic ***,as the geometry of an assembly interface is formed by one or more adjacent faces on each model,a face-attributed adjacency graph integrated with face structure fingerprint is *** can describe each CAD model as well as its assembly interfaces *** that,aided by the above descriptor,an improved graph attention network is developed based on a new dual-level anti-interference filtering mechanism,which makes it have the great potential to identify all representative kinds of assembly interface faces with high accuracy that have various geometric shapes but consistent kinematic ***,based on the abovementioned graph and face-adjacent relationships,each assembly interface on a model can be ***,experiments on representative CAD models are implemented to verify the effectiveness and characteristics of the proposed *** results show that the average assembly-interface-face-identification accuracy of the proposed approach can reach 91.75%,which is about 2%–5%higher than those of the recent-representative graph neural ***,compared with the state-of-the-art methods,our approach is more suitable to identify the assembly interfaces(with various shapes)for each individual CAD model that has typical kinematic pairs.

关键词： Assembly interface identification kinematic semantics reconstruction attributed adjacency graph graph neural network

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