On-line stability monitoring of BWR's using artificial neural networks

被引：0

作者：

Tambouratzis, T ^{[1
]}

Antonopoulos-Domis, M ^{[1
]}

机构：

[1] NCSR Demokritos, Inst Nucl Technol Radiat Protect, Athens 15310, Greece

来源：

ANNALS OF NUCLEAR ENERGY | 1999年 / 26卷 / 14期

关键词：

D O I：

暂无

中图分类号：

TL [原子能技术]; O571 [原子核物理学];

学科分类号：

0827 ; 082701 ;

摘要：

The problem of uncovering stability parameters of Boiling Water Reactors (BWRs) from short neutron noise records for on-line monitoring is investigated. The aim is to use the smallest possible number of points of the auto-correlation function (ACF) at the shortest possible time lags as input to a number of backpropagation artificial neural networks (BP ANNs), which are trained to approximate the relationship that exists between the ACF of the neutron noise signals and the stability parameters of interest (e.g. the decay ratio (DR)). Tests on novel ACFs illustrate the potential of the proposed approach for on-line stability monitoring. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：1287 / 1302

页数：16

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