<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>14(1)</volume><submitter>Li H</submitter><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</pubmed_abstract><journal>Scientific reports</journal><pagination>14697</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11208593</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy.</pubmed_title><pmcid>PMC11208593</pmcid><pubmed_authors>Li H</pubmed_authors><pubmed_authors>Fu Y</pubmed_authors><pubmed_authors>Yan S</pubmed_authors></additional><is_claimable>false</is_claimable><name>Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy.</name><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</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Jun</publication><modification>2025-04-04T20:47:19.954Z</modification><creation>2024-11-21T05:48:42.977Z</creation></dates><accession>S-EPMC11208593</accession><cross_references><pubmed>38926441</pubmed><doi>10.1038/s41598-024-65545-9</doi></cross_references></HashMap>