Subspace-based Fault Detection and Isolation Methods - Application to Vibration Monitoring

Michèle Basseville 1 Maher Abdelghani 1 Albert Benveniste 1
1 SIGMA2 - Signal, models, algorithms
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : We address the problem of detecting and isolating faults modeled as changes in the eigenstructure of a linear dynamical system. The purpose of the paper is to describe and analyze new fault detection and isolation algorithms, based on recent stochastic subspace-based identification methods and the statistical local approach to the design of detection algorithms. The application to vibration monitoring of mechanical structures and rotating machines is discussed. A conceptual comparison is made with another detection algorithm based on the instrumental variables identification method, and previously proposed by two of the authors.
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Rapport
[Research Report] RR-3299, INRIA. 1997
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https://hal.inria.fr/inria-00073389
Contributeur : Rapport de Recherche Inria <>
Soumis le : mercredi 24 mai 2006 - 12:41:08
Dernière modification le : jeudi 11 janvier 2018 - 06:20:10
Document(s) archivé(s) le : dimanche 4 avril 2010 - 23:44:54

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Michèle Basseville, Maher Abdelghani, Albert Benveniste. Subspace-based Fault Detection and Isolation Methods - Application to Vibration Monitoring. [Research Report] RR-3299, INRIA. 1997. 〈inria-00073389〉

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