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Towards an Integrated Approach for Micro Gas Turbine Fleet Monitoring, Control and Diagnostics
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. (SOFIA - Simulation and Optimisation for Future Industrial Applications)
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-6101-2863
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-3610-4680
Micro Turbine Technology bv, Eindhoven, Netherlands.
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Real-time engine condition monitoring and fault diagnostics results in reduced operating and maintenance costs and increased component and engine life. Prediction of faults can change the maintenance model of a system from a fixed maintenance interval to a condition based maintenance interval, further decreasing the total cost of ownership of a system. Technologies developed for engine health monitoring and advanced diagnostic capabilities are generally developed for larger gas turbines, and generally focus on a single system; no solutions are publicly available for engine fleets. This paper presents a concept for fleet monitoring finely tuned to the specific needs of micro gas turbines. The proposed framework includes a physics-based model and a data-driven model with machine learning capabilities for predicting system behaviour, combined with a diagnostic tool for anomaly detection and classification. The integrated system will develop advanced diagnostics and condition monitoring for gas turbines with a power output under 100 kW.

Place, publisher, year, edition, pages
2018.
National Category
Aerospace Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-43169OAI: oai:DiVA.org:mdh-43169DiVA, id: diva2:1305967
Conference
Global Power and Propulsion Forum 2018, Zurich, Switzerland
Available from: 2019-04-21 Created: 2019-04-21 Last updated: 2019-06-03Bibliographically approved

Open Access in DiVA

fulltext(4141 kB)41 downloads
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File name FULLTEXT01.pdfFile size 4141 kBChecksum SHA-512
359e6afb714304483a1891e0c2448c2807aeb4d9d13080bbea1c9de67849cf5e48cc9b3ca7d115482ba58986551a459a877101bcf89e0e81b97cd7bc312c0a70
Type fulltextMimetype application/pdf

Authority records BETA

Aslanidou, IoannaZaccaria, ValentinaRahman, MoksadurOlsson, TomasKyprianidis, Konstantinos

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other locale
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Output format
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