A transfer function approach to fault diagnosis for linear systems: inversion and low-pass filters

The purpose of this paper is to propose a simple design method for fault detection and isolation (FDI) based on model inversion and low-pass filters. Motivated by practical situations, a tradeoff between desired fast responses of fault indicating signals and robustness in the presence of disturbances is considered. We point out plain frequency design rules and basic limitations of residual generation. Computations of inverse models are easy to implement by means of a symbolic algebraic language. Several illustrative examples show the performance of the proposed FDI scheme.

[1]  P. Frank,et al.  Fault detection via factorization approach , 1990 .

[2]  F. Szigeti,et al.  SYSTEM INVERSION AND FAULT DETECTION : THE FAILURE AFFINE NONLINEAR CASE , 2002 .

[3]  M. Sain.  Finite dimensional linear systems , 1972 .

[4]  Yixin Diao,et al.  Stable fault-tolerant adaptive fuzzy/neural control for a turbine engine , 2001, IEEE Trans. Control. Syst. Technol..

[5]  M. Fliess.  An algebraic approach to fault diagnosis for linear systems , 2003 .

[6]  Erik Frisk,et al.  Using minimal polynomial bases for fault diagnosis , 1999, 1999 European Control Conference (ECC).

[7]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[8]  Richard D. Braatz,et al.  On the "Identification and control of dynamical systems using neural networks" , 1997, IEEE Trans. Neural Networks.

[9]  Marios M. Polycarpou,et al.  Learning methodology for failure detection and accommodation , 1995 .

[10]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[11]  Hiroshi Seki,et al.  Abnormal Event Identification in Nuclear Power Plants Using a Neural Network and Knowledge Processing , 1993 .

[12]  Ron J. Patton,et al.  Input Observability and Input Reconstruction , 1998, Autom..

[13]  ADDISON RIOS-BOLIVAR,et al.  A FDI Filter Based-on Inversion for Nonlinear Systems , .

[14]  J. F. Davis,et al.  An expert system approach to malfunction diagnosis in chemical plants , 1988 .

[15]  Germain Garcia,et al.  ON FDI FILTERS AND SYSTEM INVERTIBILITY , 2002 .

[16]  Addison Ríos,et al.  Fault Detection and Isolation Filter Design by Inversion: The Case of Linear Systems , 2000 .

[17]  M. Massoumnia.  A geometric approach to the synthesis of failure detection filters , 1986 .

[18]  Kenneth A. Loparo,et al.  A neural-network approach to fault detection and diagnosis in industrial processes , 1997, IEEE Trans. Control. Syst. Technol..