System modelling approach for fault detection in nonlinear systems

This paper addresses the issue of system modelling for fault detection in nonlinear systems. In many practical situations a primary model (physical model or linearized model) of a nonlinear system already exists. In such cases, we propose to build an auxiliary model that drives the residual of the combined (primary plus auxiliary) model to zero during fault-free operation. The auxiliary model can be built by any data-driven technique in real time. Once the auxiliary model is built and the combined residual converges to zero, the model parameters are kept constant; after this, the model can be used as the basis for fault detection in the original nonlinear system. Simulation shows that the proposed scheme is effective and has potential application ability in fault detection and identification (FDI).