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Prognostic Hybrid Model From Data Fusion on Machine Tools
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-4107-0991
2015 (English)In: Proceedings of the XXI IMEKO World Congress: Prague, Czech Republic, 2015, Prague: IMEKO , 2015Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes an enhancement of RUL prediction method based on degradation trajectory tracking under the scope of machine tools. The operational condition data of the machine over time provides the potential degradation state at the next estimation iteration step, based on data-driven techniques. The model-based approach is considered as long-term prognostics method assuming that aphysical model describing the degradation behaviour is available. Fusing the aforementioned techniques outputs a hybrid model for RUL estimation

Place, publisher, year, edition, pages
Prague: IMEKO , 2015.
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-39207Scopus ID: 84951095353Local ID: dda54248-e9ab-4fe2-a5a0-18700907bcd6ISBN: 978-80-01-05793-3 (electronic)OAI: oai:DiVA.org:ltu-39207DiVA: diva2:1012716
Conference
IMEKO World Congress : 30/08/2015 - 04/09/2015
Note
Godkänd; 2015; 20151007 (diegal)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved

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