A new fault-detection system for nonlinear systems based on an interval fuzzy model

The paper proposes a new fault-detection scheme for nonlinear input-output systems with uncertain interval-type parameters. Using a high-pass filter for detecting the system's steady-state conditions, one is able to build a confidence band of data for the system in normal operating mode. The band can be seen as an approximation of the system's nonlinear input-output mapping including the effects of uncertainties. By approximating the boundary functions of the band using an interval fuzzy model (INFUMO), we are able to build a simple and effective fault-detection system based on the boundary-crossing test and logical relations. An example of a fault-detection system for a pH neutralization process is presented to demonstrate the benefits of the proposed method.