Fault detection and isolation for a three tank system based on a bilinear model of the supervised process

Time varying innovation generators combined with generalized likelihood ratio (GLR) tests are designed for detection and isolation of faults in a three tank system. This diagnosis system is based on a bilinear model of the supervised process. It is shown to work properly in a larger working range than a fault detection and isolation (FDI) system based on a linear model. As the faults enter in a bilinear way in the model, achieving exact de-coupling of the residuals with respect to some of the faults is not possible. One has to resort to approximation methods such as the approach developed in Patton and Chen [4]. The whole FDI system is designed and tuned on the basis of a simulation of the three tank system, Next it is applied to actual pilot: plant data and it is shown to perform well. To be able to detect temporary faults (namely fault appearance and disappearance) with the GLR test, a strategy based on the use of two Kalman filters running in parallel is used.