Physics-informed self-supervised diagnosis of rotating machinery using latent ODEs and transformer encoders.
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| Title: | Physics-informed self-supervised diagnosis of rotating machinery using latent ODEs and transformer encoders. |
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| Authors: | Amin MA; MS in Information Technology, St. Francis College, Brooklyn, New York, United States of America., Ahsan MS; MSc in IT Project Management, School of Professional Studies, Clark University, Worcester, Massachusetts, United States of America., Maua J; Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh., Ahmed M; Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh., Nur K; Department of Computer Science, American International University-Bangladesh, Dhaka, Bangladesh. |
| Source: | PloS one [PLoS One] 2026 Feb 02; Vol. 21 (2), pp. e0339239. Date of Electronic Publication: 2026 Feb 02 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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