Computation and monitoring of the deviations of gas turbine unmeasured parameters

One of the principle purposes of gas turbine diagnostics is the estimation and monitoring of important unmeasured quantities such as engine thrust, shaft power, and engine component efficiencies. There are simple methods that allow computing the unmeasured parameters using measured variables and gas turbine thermodynamics. However, these parameters are not good diagnostic indices because they strongly depend on engine operating conditions but in a less degree are influenced by engine degradation and faults. In the case of measured gas path variables, deviations between measurements and an engine steady state baseline were found to be good indicators of engine health. In this paper, the deviation computation and monitoring are extended to the unmeasured parameters. To verify this idea, the deviations of compressor and turbine efficiencies as well as a high pressure turbine inlet temperature are examined. Deviation computations were performed at steady states for both baseline and faulty engine conditions using a nonlinear thermodynamic model and real data. These computational experiments validate the utility of the deviations of unmeasured variables for gas turbine monitoring and diagnostics. The thermodynamic model is used in this paper only to generate data, and the proposed algorithm for computing the deviations of unmeasured parameter can be considered to be a data-driven technique. This is why the algorithm is not affected by inaccuracies of a physics-based model, is not exigent to computer resources, and can be used in on-line monitoring systems.