Robust fault diagnosis of dynamic processes using parametric identification with eigenstructure assignment approach

Abstract

Presents some results concerning robust fault diagnosis of dynamic processes using a parametric identification technique. The first step of the considered approach estimates an equation error model by means of the input-output data acquired from the monitored system. In particular, the equation error term of the model takes into account disturbances, non-linear and time-variant terms, measurement errors, etc. The next step of the method requires a state-space realization of the input-output equation error model which allows us to define an equivalent disturbance distribution matrix related to the error term. Therefore, the eigenstructure assignment results for robust fault diagnosis can be successfully applied. The proposed procedure has been tested by means of a industrial process simulator. In such a manner, sensor, component and actuator faults can be simulated on an single shaft gas turbine. Results from this simulator are also reported.