A model-based ensemble approach to plant-wide online sensor monitoring
by Giulio Gola, Davide Roverso, Mario Hoffmann
International Journal of Nuclear Knowledge Management (IJNKM), Vol. 5, No. 2, 2011

Abstract: Online sensor monitoring aims at detecting anomalies in sensors and reconstructing their correct signals during operation. Since 1994, research at the OECD Halden Reactor Project has focused on the problem of sensor monitoring, eventually developing the PEANO system for signal validation. PEANO combines fuzzy clustering and auto-associative neural networks and has proved successful in a variety of practical applications. Nevertheless, using one single empirical model sets a limit to the number of signals that can be handled at a time. Recently, PEANO has been extended to cover the validation of all the plant signals. This has entailed shifting from a single-model to a model-ensemble approach. This paper illustrates the plant-wide extension of the PEANO system and its practical application to a real case study.

Online publication date: Wed, 18-Feb-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Nuclear Knowledge Management (IJNKM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com