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Automatic CAD Assemblies Generation by Linkage Graph Overlay for Machine Learning Applications

Article dans une revue avec comité de lecture
Auteur
VERGEZ, Lucas
ccPERNOT, Jean-Philippe
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
ccPOLETTE, Arnaud

URI
http://hdl.handle.net/10985/22982
DOI
10.14733/cadaps.2022.722-732
Date
2021-11-29
Journal
Computer-Aided Design and Applications

Résumé

This paper introduces an approach to synthetize new CAD assemblies from existing STEP files. The algorithm first generates linkage graph by detecting linkage between components. Then it detects linkages similarities between components of different assemblies while analyzing the associated graphs. Finally, it exchanges the similar components. The similarities in a family of components must be formalized by the user. Then the similar components can be replaced by the other through smart placements. This method allows to automatically generate a wide variety of new consistent assemblies sharing the same semantics, in order to create databases of CAD assemblies ready for machine learning applications. It has been validated on several cases.

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  • Laboratoire d’Ingénierie des Systèmes Physiques Et Numériques (LISPEN)

Documents liés

Visualiser des documents liés par titre, auteur, créateur et sujet.

  • Automatic CAD Assemblies Generation by Linkage Graph Overlay for Machine Learning Applications 
    Communication avec acte
    VERGEZ, Lucas; ccPERNOT, Jean-Philippe; ccPOLETTE, Arnaud (CAD, 2021-07-05)
    Enlarging 3D model databases by shape synthesis is a large field of research. Indeed, the use of machine learning techniques requires a huge amount of labeled CAD models, and it is therefore crucial to rely on large ...
  • Multi-part kinematic constraint prediction for automatic generation of CAD model assemblies using graph convolutional networks 
    Article dans une revue avec comité de lecture
    VERGEZ, Lucas; ccPOLETTE, Arnaud; ccPERNOT, Jean-Philippe (Elsevier BV, 2025-01)
    This paper presents a machine learning-based approach to predict kinematic constraints between CAD models that have potentially never been assembled together before. During the learning phase, the algorithm is trained ...
  • Interface-Based Search and Automatic Reassembly of CAD Models for Database Expansion and Model Reuse 
    Article dans une revue avec comité de lecture
    VERGEZ, Lucas; ccPOLETTE, Arnaud; ccPERNOT, Jean-Philippe (Elsevier BV, 2024-02)
    This paper introduces a new framework for reassembling CAD models of mechanical parts. The generated CAD assemblies are well-constrained, with collision-free parts, and they are ready-to-use for downstream applications. ...
  • Survey on the View Planning Problem for Reverse Engineering and Automated Control Applications 
    Article dans une revue avec comité de lecture
    PEUZIN-JUBERT, Manon; NOZAIS, Dominique; MARI, Jean-Luc; ccPERNOT, Jean-Philippe; ccPOLETTE, Arnaud (Elsevier BV, 2021-12)
    At present, optical sensors are being widely used to realize high quality control or reverse engineering of products, systems, buildings, environments or human bodies. Although the intrinsic characteristics of such ...
  • A Data Structure for Developing Data-Driven Digital Twins 
    Ouvrage scientifique
    ORUKELE, Oghenemarho; ccPOLETTE, Arnaud; GONZALEZ LORENZO, Aldo; MARI, Jean-Luc; ccPERNOT, Jean-Philippe (Springer Nature Switzerland, 2024-06)
    Digital twins have the potential to revolutionize the way we design, build and maintain complex systems. They are high-fidelity representations of physical assets in the digital space and thus allow advanced simulations ...

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