There exist many approaches for gas turbine engine condition monitoring and fault diagnosis. Among them, gas path analysis depends on the relations between deviations of performance parameters and deviations of measurements, such as pressure, temperature, at some positions in the flow path. A dynamic tracking filter combined with a nonlinear gas turbine model can be used to implement a fault detection system. The dynamic tracking filter is composed with multiple feedback loops in which the residuals between model output and measurement are driven to zero by adjusting the performance parameters. In many cases, the number of measurement parameters is less than that of performance parameters, which impose a limit on the application of tracking filter in practical situations. In the present study, the tracking filter is retrofitted to be driven by the error between state of the model and the estimated state reconstructed from the engine measurement. For the time being, only linear time-invariant (LTI) state observer is considered. A nonlinear simulation model of the heavy-duty gas turbine under study is used to derive the linear system model needed for the design of LTI state observer. Input vector and output vector are chosen according to the practical situations. The linear system model obtained around the nominal operating point is observable, so a state observer can be designed. With 6 state variables observable from the engine, 6 performance parameters can be tracked with the proper design of tracking filter. The structure of the tracking filter consists of a static decoupling matrix DM and in series with 6 PI controllers.

Deviations of performance parameters are implanted into the gas turbine model by scaling the performance maps used; and then simulation results are taken as measurements needed for the tracking filter to run. Tracking results of performance parameters in different cases are given to show the tracking capability for isolated performance deviations and concurrent performance deviations.

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