An approach to optimally robust fault detection and diagnosis

Author

Nazih, Mechbal ; Michel, Vergé

Author_Institution

Lab. de Mecanique des Systemes et des Procedes, ENSAM, Paris, France

fYear

2001

fDate

2001

Firstpage

94

Lastpage

100

Abstract

In this paper, an original approach for robust fault detection and diagnosis (RFDD) is presented. We propose a method that makes use of H ₂ and H_∞ polynomial estimators to elaborate a RFDD procedure. The system considered is linear, stochastic and subject to noise, unknown inputs and uncertainties. The residual is obtained via factorization approach and then parameterized by H₂ and H_∞ polynomial estimators to generate optimal robust fault detectors (ORFD). Adaptive thresholds are also derived with respect to an evaluation index. The results are illustrated by simulations on an actual rolling system

Keywords

H^∞ optimisation; fault diagnosis; identification; linear systems; noise; stochastic systems; uncertain systems; H_∞ polynomial estimators; H₂ polynomial estimators; ORFD; RFDD; adaptive thresholds; evaluation index; factorization; linear stochastic system; noise; optimal robust fault detectors; optimally robust fault diagnosis; rolling system; uncertainties; unknown inputs; Fault detection; Fault diagnosis; Hydrogen; Mathematical model; Noise robustness; Polynomials; Signal processing; Stochastic resonance; Stochastic systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 2001. (CCA '01). Proceedings of the 2001 IEEE International Conference on

Conference_Location

Mexico City

Print_ISBN

0-7803-6733-2

Type

conf

DOI

10.1109/CCA.2001.973844

Filename

973844