Sodium boiling Detection in a LMFBR Using Autoregressive Models and SVM

Bose, Tanmoy; Geraldo, Issa Cherif; Pekpe, Midzodzi; Cassar, Jean Philippe; Mohanty, Amiya Rajan; Paumel, Kevin

Document type :

Communication dans un congrès avec actes

Title :

Sodium boiling Detection in a LMFBR Using Autoregressive Models and SVM

Author(s) :

Bose, Tanmoy [Auteur]
Indian Institute of Technology Kharagpur [IIT Kharagpur]
Geraldo, Issa Cherif [Auteur]
Systèmes Tolérants aux Fautes [STF]
Pekpe, Midzodzi [Auteur]

Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Cassar, Jean Philippe [Auteur]
Systèmes Tolérants aux Fautes [STF]
Mohanty, Amiya Rajan [Auteur]
Indian Institute of Technology Kharagpur [IIT Kharagpur]
Paumel, Kevin [Auteur]
CEA Cadarache

Conference title :

IFAC World Congress 214

City :

Cape Town

Country :

Afrique du Sud

Start date of the conference :

2014-08-24

Book title :

Fault detection and isolation, switching systems, discernability and distinguishability

Publication date :

2014-08-24

HAL domain(s) :

Sciences de l'ingénieur [physics]/Automatique / Robotique

English abstract : [en]

This paper deals with acoustic detection of sodium boiling in a Liquid Metal Fast Breeder Reactor (LMFBR) cooled by liquid sodium. As sodium boiling induces acoustic emission, the method consists in real time analysis of ...
Show more >This paper deals with acoustic detection of sodium boiling in a Liquid Metal Fast Breeder Reactor (LMFBR) cooled by liquid sodium. As sodium boiling induces acoustic emission, the method consists in real time analysis of acoustic signals measured through wave guides. AutoRegressive (AR) models are estimated on sliding windows and are classified in boiling or non-boiling models using Support Vector Machines (SVM). One of the difficulties to cope with is disturbances due to the influence of some environment noises like the liquid coolant cavitation, vortex flow, shaft vibration and mechanical pump noise. These disturbances can generate false alarms or mask the boiling. The proposed method is designed to be robust toward these disturbances. Furthermore, the SVM are designed to be robust toward the operating mode changing. The application for online monitoring is made on data obtained from French nuclear power plant Phenix and boiling sound signals generated from Laboratory experiments. Different acoustic boiling sound levels are used and the effectiveness of the method is shown by the good detection rate and its low false alarm rate even for low acoustic boiling sound level.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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