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Enhanced Sensor Placement Optimization and Defect Detection in Structural Health Monitoring Using Hybrid PI-DEIM Approach.

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第一作者： Minyoung,Yun

第一单位： PIMM Research Laboratory, UMR 8006 CNRS-ENSAM-CNAM, Arts et Metiers Institute of Technology, 151 Boulevard de l'Hôpital, 75013 Paris, France.

作者： Minyoung,Yun ^[1] ; Mikhael,Tannous ^[1] ; Chady,Ghnatios ^[2] ; Eivind,Fonn ^[3] ; Trond,Kvamsdal ^[4] ; Francisco,Chinesta ^[5]

作者单位： PIMM Research Laboratory, UMR 8006 CNRS-ENSAM-CNAM, Arts et Metiers Institute of Technology, 151 Boulevard de l'Hôpital, 75013 Paris, France. ^[1] Mechanical Engineering Department, University of North Florida, 1 UNF Drive, Jacksonville, FL 32224, USA. ^[2] Department of Mathematics and Cybernetics, SINTEF Digital, Kloebuveien 153, 7465 Trondheim, Norway. ^[3] Department of Mathematics and Cybernetics, SINTEF Digital, Kloebuveien 153, 7465 Trondheim, Norway.;Department of Mathematical Sciences, Norwegian University of Science and Technology, Alfred Getz' vei 1, 7491 Trondheim, Norway. ^[4] PIMM Research Laboratory, UMR 8006 CNRS-ENSAM-CNAM, Arts et Metiers Institute of Technology, 151 Boulevard de l'Hôpital, 75013 Paris, France.;CNRS@CREATE Ltd., 1 Create Way, #08-01 CREATE Tower, Singapore 138602, Singapore. ^[5]

关键词 discrete empirical interpolation method machine learning optimal sensor placement random permutation features importance method

DOI 10.3390/s25010091

PMID 39796881

发布时间 2025-01-13

基金项目

//dthor.eu/)./Grant 320 agreement 101103257 dTHOR-EDF-2021-NAVALR-2 (https/This project has received funding from the European Defense Fund (EDF) under grant 320 agreement 101103257 dTHOR-EDF-2021-NAVALR-2 (https

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