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PFSDS026

Data science based wear prediction

Grant period18 months
Funding bodyExploratory Research Space der RWTH Aachen
 ERS
IdentifierG:(DE-82)EXS-PF-PFSDS026

Exploratory Research Space: Prep Fund als Anschubfinanzierung zur Schließung strategischer Lücken

 

Recent Publications

All known publications ...
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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;
Mean-field and kinetic descriptions of neural differential equations
Foundations of data science : FoDS 4(2), 271-298 () [10.3934/fods.2022007]  GO BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article/Contribution to a conference proceedings  ;  ;  ;  ;  ;
Data-driven wear monitoring for sliding bearings using acoustic emission signals and long short-term memory neural networks
23. International Conference on Wear of Materials, onlineonline, 26 Apr 2021 - 29 Apr 20212021-04-262021-04-29 Wear 476, 203616 () [10.1016/j.wear.2021.203616] special issue: "Special issue: 23rd International Conference on Wear of Materials / guest editor: Martin Dienwiebel"  GO BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;
Machine learning based anomaly detection and classification of acoustic emission events for wear monitoring in sliding bearing systems
Tribology international 155, 106811 () [10.1016/j.triboint.2020.106811]  GO BibTeX | EndNote: XML, Text | RIS

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Simplified ResNet approach for data driven prediction of microstructure-fatigue relationship
Mechanics of materials 151, 103625 () [10.1016/j.mechmat.2020.103625]  GO BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings  ;  ;
Koppelung von KI-Methoden und AVL EXCITE™ Power Unit zur Verschleißprognose von Gleitlagern
AVL Virtual German Simulation Conference 2020 – Proceedings
AVL Virtual German Simulation Conference 2020, onlineonline, 22 Sep 2020 - 24 Sep 20202020-09-222020-09-24
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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings  ;  ;  ;
Machine Learning based condition monitoring and anomaly detection for wear lifetime prediction of journal bearing drivetrains
[TAE: 22nd International Colloquium Tribology - Industrial and Automotive Lubrication]
TAE: 22. International Colloquium Tribology - Industrial and Automotive Lubrication, Meeting location,
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All known publications ...
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 Record created 2019-11-16, last modified 2023-01-24



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