FAULT DETECTION BY NEURO-FUZZY IDENTIFICATION IN A NONLINEAR SYSTEM

This paper describes a fault detection and identification method, based on the parity equations approach, to be applied to nonlinear systems. The input-output nonlinear model of the plant, used in the method, has been obtained by a neural fuzzy inference system. The method proposed is able to detect both abrupt and incipient faults. This method has been applied with good performance to a real industrial pilot plant for fault detection in a level sensor.