Deviation problem in gas turbine health monitoring

This paper looks at the deviations forming as differences between actual measurements and a normal state function for further application in gas turbine monitoring, diagnostics, and forecasting. The focus of the paper is possible greatest reducing the deviation random errors in order to observe more clearly the trends and to detect corresponding gas turbine faults. Possible error sources are examined and some methods are proposed to enhance the normal function and the deviations. Real maintenance data and gas turbine nonlinear thermodynamic model are applied to realize and verify these methods.