Estimation and monitoring of unmeasured gas turbine variables

Abstract

This work proposes a universal data-driven approach to compute and monitor gas turbine unmeasured variables. To this end, a large amount of unmeasured and measured data is first computed at steady state for both baseline and faulty engine conditions using a nonlinear thermodynamic model. On the data generated, polynomial models that relate the unmeasured quantities with the measured variables are then determined. These data-driven models allow the computation of unmeasured variables and their deviations. Accuracy analysis is conducted separately for baseline and current estimates of unmeasured variables and for deviation estimates. All the results prove that the estimates are exact enough. Thus it is possible to obtain a universal fast and accurate method for computing important unmeasured gas turbine quantities that is suitable for practical applications. The method promises a drastic increase in the diagnostic capabilities of online monitoring systems.