Dynamic Fuzzy Model based Fault Diagnosis System and it's Application

동적퍼지모델기반 고장진단 시스템 및 응용

This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the nonlinear system. The dynamic behavior of a nonlinear system is represented by a set of local linear models. The parameters of the DFM are identified in on-line and aggregated to generate a residual vector by the approximate reasoning. The neural network classifer learns the relationship between the residual vector and fault type and used both for the detection and isolation of process faults We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.