Fault Diagnosis of a Simulated Industrial Gas Turbine via Identification Approach

In this paper, a model-based procedure exploiting the analytical redundancy principle for the detection and isolation of faults on a simulated process is presented. The main point of the work consists of using an identification scheme in connection with dynamic observer and Kalman filter designs for diagnostic purpose. The errors-in-variables identification technique and output estimation approach for residual generation are in particular advantageous in terms of solution complexity and performance achievement. The proposed tools are analysed and tested on a single-shaft industrial gas turbine MATLAB/ SIMULINK1 simulator in the presence of disturbances, i.e. measurement errors and modelling mismatch. Selected performance criteria are used together with Monte-Carlo simulations for robustness and performance evaluation. The suggested technique can constitute the design methodology realising a reliable approach for real application of industrial process FDI.