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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| 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 |