System state monitoring using recurrent local learning machine

G - Physics – 01 – M

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G01M 99/00 (2011.01) G06F 17/16 (2006.01) A61B 5/00 (2006.01) G01M 15/14 (2006.01)

Patent

CA 2505026

Reference data observations for a given system are used to develop a reference set (102) of such observations. Subsequent observations (comprising, in one embodiment, current observations) (107) are then used to facilitate selection of portions of this reference set to yield a resultant set of observations (118) that serves as a model. This model can then be used in comparison to actual system performance to detect, for example, a trend towards a faulty condition. Pursuant to a preferred approach, the model is recomputed from time to time and, pursuant to a particular embodiment, is recomputed with each new set of current observations.

Selon l'invention, des observation de données de référence pour un système donné sont utilisés pour développer un ensemble de référence (102) desdites observations. Des observations supplémentaires (comprenant, dans un mode de réalisation, des observations courantes) (107) sont utilisées pour faciliter la sélection de parties de l'ensemble de référence, ce qui permet de rendre un ensemble résultant d'observations (118) qui sert de modèle. Ce modèle peut être utilisé par comparaison à des performances de systèmes actuels pour détecter, par exemple, une tendance vers un état défectueux. Selon une approche préférée, Le modèle est recalculé avec un nouvel ensemble d'observations courantes.

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