A Flexible Approach for Retrieving Geometrically Similar Finite Element Models Using Point Cloud Autoencoders

Sonja Schlenz, Simon Mößner, Carl Henrik Ek, Fabian Duddeck

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

For the development of complex products like vehicle components, knowledge about previous solutions is a key factor. Complete solutions or parts thereof can often be reused if a similar previous model can be identified. To gain independence from the individual experience of single engineers about previous models and a tedious search process, identifying and retrieving the most similar models from large databases offers great potential. Accordingly, this paper introduces a method to achieve this kind of shape retrieval based on engineering data. 3D geometries are represented as point clouds and reduced to one single vector with an autoencoder to identify similarities in the latent space. The method can be used in a flexible way to identify global or local similarities as well as to emphasize different parts of the structure in the similarity search. The method is evaluated on an industrial dataset containing real-world engineering data.

OriginalspracheEnglisch
Titel15th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of IC3K 2023 - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Redakteure/-innenAna Fred, Frans Coenen, Jorge Bernardino
Herausgeber (Verlag)Science and Technology Publications, Lda
Seiten188-195
Seitenumfang8
ISBN (elektronisch)9789897586712
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung15th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023 - Hybrid, Rome, Italien
Dauer: 13 Nov. 202315 Nov. 2023

Publikationsreihe

NameInternational Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K - Proceedings
Band1
ISSN (elektronisch)2184-3228

Konferenz

Konferenz15th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023
Land/GebietItalien
OrtHybrid, Rome
Zeitraum13/11/2315/11/23

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