3D Scanner-Based Identification of Welding Defects—Clustering the Results of Point Cloud Alignment

This paper describes a framework for detecting welding errors using 3D scanner data. The proposed approach employs density-based clustering to compare point clouds and identify deviations. The discovered clusters are then classified according to standard welding fault classes. Six welding deviations...

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Detalles Bibliográficos
Autores principales: Hegedűs-Kuti, János, Szőlősi, József, Varga, Dániel, Abonyi, János, Andó, Mátyás, Ruppert, Tamás
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007542/
https://www.ncbi.nlm.nih.gov/pubmed/36904704
http://dx.doi.org/10.3390/s23052503

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007542/
https://www.ncbi.nlm.nih.gov/pubmed/36904704
http://dx.doi.org/10.3390/s23052503

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