{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["14(1)"],"submitter":["Li H"],"pubmed_abstract":["Laser powder bed fusion (LPBF) is an additive manufacturing technology with high practical value. In order to improve the quality of the fabricated parts, process monitoring has become a crucial solution, offering the potential to ensure manufacturing stability and repeatability. However, a cardinal challenge involves discerning a precise correlation between process characteristics and potential defects. This paper elucidates the integration of an off-axis vision monitoring mechanism via a high-speed camera focused on capturing the single-track melting phenomenon. An innovative image processing method was devised to segment the plume and spatters, while Kalman filter was employed for multi-object tracking of the spatters. The features of both the plume and spatters were extracted, and thei"],"journal":["Scientific reports"],"pagination":["14697"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11208593"],"repository":["biostudies-literature"],"pubmed_title":["Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy."],"pmcid":["PMC11208593"],"pubmed_authors":["Li H","Fu Y","Yan S"],"additional_accession":[]},"is_claimable":false,"name":"Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy.","description":"Laser powder bed fusion (LPBF) is an additive manufacturing technology with high practical value. In order to improve the quality of the fabricated parts, process monitoring has become a crucial solution, offering the potential to ensure manufacturing stability and repeatability. However, a cardinal challenge involves discerning a precise correlation between process characteristics and potential defects. This paper elucidates the integration of an off-axis vision monitoring mechanism via a high-speed camera focused on capturing the single-track melting phenomenon. An innovative image processing method was devised to segment the plume and spatters, while Kalman filter was employed for multi-object tracking of the spatters. The features of both the plume and spatters were extracted, and thei","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jun","modification":"2025-04-04T20:47:19.954Z","creation":"2024-11-21T05:48:42.977Z"},"accession":"S-EPMC11208593","cross_references":{"pubmed":["38926441"],"doi":["10.1038/s41598-024-65545-9"]}}