Several operating parameters for the control and protection of the units are acquired by the control and protection systems used in industrial applications. The use of these parameters in conjunction of physical models, empirical models and transfer functions (that represent digital replicas of the engine) allows for a broader scope of condition monitoring, taking into account the wing to wing process which spans from data acquisition to end user actionable insight. This paper describes 3 specific cases: 1) an algorithm based on the performance model of the overall GT used to monitor the axial compressor degradation and optimize the planned axial compressor water wash of an aero-derivative GT; 2) an analytic based on the flow function physic model used to monitor the clogging of the fuel nozzles in a heavy duty GT and to plan their maintenance; 3) an analytic based on a hybrid model used to monitor the axial thrust acting on a roller bearing of an aero-derivative GT and used to verify the status of the bearing and to plan its maintenance. Moreover, the paper provides details about the evaluation of the measurements, describes the model accuracy and explains how the results obtained are affected by these uncertainties and the methods used to mitigate these uncertainties. In addition, this paper shows a method to aggregate and weigh the monitoring of each single component and its own status into an overall health view.
- International Gas Turbine Institute
Use of Operating Parameters, Digital Replicas and Models for Condition Monitoring and Improved Equipment Health
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Carlevaro, F, Cioncolini, S, Sepe, M, Parrella, I, Allegorico, C, De Stefanis, L, Mastroianni, M, & Escobedo, E. "Use of Operating Parameters, Digital Replicas and Models for Condition Monitoring and Improved Equipment Health." Proceedings of the ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy. Oslo, Norway. June 11–15, 2018. V009T27A026. ASME. https://doi.org/10.1115/GT2018-76849
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