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Towards an Integrated Approach for Micro Gas Turbine Fleet Monitoring, Control and Diagnostics
Mälardalen University, Sweden.
Mälardalen University, Sweden.
Mälardalen University, Sweden.
Mälardalen University, Sweden.
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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
Engineering and Technology
Identifiers
URN: urn:nbn:se:ri:diva-37596OAI: oai:DiVA.org:ri-37596DiVA, id: diva2:1283135
Conference
Global Power and Propulsion Society (GPPS), Zurich (10th-12th January 2018)
Available from: 2019-01-28 Created: 2019-01-28 Last updated: 2019-03-07Bibliographically approved

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http://fudipo.eu/wp-content/uploads/2018/03/Art%C3%ADculo-GPPS.pdf

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Olsson, Tomas

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