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Prognosis of Journal Bearing Wear Using Machine Learning-Based Surrogate Models for Predictive Maintenance

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In
Conference proceedings : CWD 2025 : Conference for Wind Power Drives : EUROGRESS Aachen, March 11 - 12 2025, Seiten/Artikel-Nr: 266-272

Konferenz/Event:CWD 2025 Conference for Windpower Drives , Aachen , Germany , CWD 2025 , 2025-03-11 - 2025-03-12

Umfang266-272

Online
URL: https://cwd-dsec.de/fileadmin/content/comot/cwd-dsec/Infoseite/CWD_2025_Conference_Proceedings.pdf?utm_source=chatgpt.com

Einrichtungen

  1. Lehrstuhl und Institut für Maschinenelemente und Systementwicklung (411710)


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Dokumenttyp
Contribution to a conference proceedings

Format
online

Sprache
English

Anmerkung
No peer reviewed article

Interne Identnummern
RWTH-2026-00588
Datensatz-ID: 1025197

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Conference Presentation  ;  ;
Prognosis of Journal Bearing Wear Using Machine Learning-Based Surrogate Models for Predictive Maintenance
CWD 2025 Conference for Windpower Drives, CWD 2025, AachenAachen, Germany, 11 Mar 2025 - 12 Mar 20252025-03-112025-03-12  GO BibTeX | EndNote: XML, Text | RIS

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Faculty of Mechanical Engineering (Fac.4)
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411710
 Record created 2026-01-15, last modified 2026-03-03
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