Detection of bias in measurement using analytical redundancy - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 1990

Detection of bias in measurement using analytical redundancy

Résumé

The validation of signals is a technique wich integrates information from redundant and from functionally diverse sensors to provide highly reliable information to operating crews and to automatic controllers. Signal validation is generally performed by like-sensor comparisons (direct redundancy). When the increase of sensors is impossible, we use in preference analytical redundancy. Analytical redundancy refers to the physical relationships, such as conservation of mass or conservation of energy, that exist among the many variables being measured in a system. These validation techniques must be implemented to increase systems reliability and to facilitate detection of failures. This paper presents two methods of detection and location of mesaurement failures : the first is the standardized imbalance residuals approach and the second is the approach based on standardized least square residuals. These techniques are presented by using linear models that we extend to nonlinear models. We assume that all the variables are measured (redundant system), that the measurement errors are ruled by a zero mean normal distribution and known variances, and that the process model is correct.
Fichier principal
Vignette du fichier
Kratz_SAFEPROCESS_1990.pdf (840.67 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00293579 , version 1 (15-03-2014)

Identifiants

  • HAL Id : hal-00293579 , version 1

Citer

Frédéric Kratz, José Ragot, Didier Maquin, Antoine Despujols. Detection of bias in measurement using analytical redundancy. 7th International Symposium on Technical Diagnostics, Sep 1990, Helsinki, Finland. ⟨hal-00293579⟩
121 Consultations
80 Téléchargements

Partager

Gmail Facebook X LinkedIn More