Qualitative performance comparison of reactivity estimation between the extended Kalman filter technique and the inverse point kinetic method

被引:13
|
作者
Shimazu, Y. [1 ]
van Rooijen, W. F. G. [1 ]
机构
[1] Univ Fukui, Res Inst Nucl Engn, Tsuruga, Fukui T9140055, Japan
关键词
Reactivity; Inverse point kinetic; Extended Kalman filter; Noise; Reactivity fluctuation; Digital reactivity meter; CRITICALITY APPROACH; METER;
D O I
10.1016/j.anucene.2013.12.004
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 Extended Kalman Filtering (EKF) technique has been applied for estimation of subcriticality with a good noise filtering and accuracy. The Inverse Point Kinetic (IPK) method has also been widely used for reactivity estimation. The important parameters for the EKF estimation are the process noise covariance, and the measurement noise covariance. However the optimal selection is quite difficult. On the other hand, there is only one parameter in the IPK method, namely the time constant for the first order delay filter. Thus, the selection of this parameter is quite easy. Thus, it is required to give certain idea for the selection of which method should be selected and how to select the required parameters. From this point of view, a qualitative performance comparison is carried out. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:161 / 166
页数:6
相关论文
共 50 条
  • [1] Comparison of reactivity estimation performance between two extended Kalman filtering schemes
    Peng, Xingjie
    Cai, Yun
    Li, Qing
    Wang, Kan
    ANNALS OF NUCLEAR ENERGY, 2016, 96 : 76 - 82
  • [2] Comparison of reactivity estimation performance between two extended Kalman filtering schemes
    Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu, China
    不详
    Ann Nucl Energy, (76-82):
  • [3] A Performance Comparison Between Extended Kalman Filter and Unscented Kalman Filter in Power System Dynamic State Estimation
    Khazraj, Hesam
    da Silva, F. Faria
    Bak, Claus Leth
    2016 51ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2016,
  • [4] A Comparison between State of Charge Estimation Methods: Extended Kalman Filter and Unscented Kalman Filter
    Ilies, Adelina Ioana
    Chindris, Gabriel
    Pitica, Dan
    2020 IEEE 26TH INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME 2020), 2020, : 376 - 381
  • [5] Projectile trajectory estimation: performance analysis of an Extended Kalman Filter and an Imperfect Invariant Extended Kalman Filter
    Roux, Alicia
    Changey, Sebastien
    Weber, Jonathan
    Lauffenburger, Jean-Philippe
    2021 9TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC'21), 2021, : 274 - 281
  • [6] Maximum Power Point Tracking by the technique of the extended Kalman filter
    Ben Belghith, Oussama
    Sbita, Lasaad
    Bettaber, Fathia
    2017 INTERNATIONAL CONFERENCE ON GREEN ENERGY & CONVERSION SYSTEMS (GECS), 2017,
  • [7] Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system
    St-Pierre, M
    Gingras, D
    2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, 2004, : 831 - 835
  • [8] Comparison of Bingham Filter and Extended Kalman Filter in IMU Attitude Estimation
    Wang, Weixin
    Adamczyk, Peter G.
    IEEE SENSORS JOURNAL, 2019, 19 (19) : 8845 - 8854
  • [9] An extended Kalman-filter for regional scale inverse emission estimation
    Brunner, D.
    Henne, S.
    Keller, C. A.
    Reimann, S.
    Vollmer, M. K.
    O'Doherty, S.
    Maione, M.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2012, 12 (07) : 3455 - 3478
  • [10] Reactivity estimation during a reactivity-initiated accident using the extended Kalman filter
    Busquim e Silva, R.
    Marques, A. L. F.
    Cruz, J. J.
    Shirvan, K.
    Kazimi, M. S.
    ANNALS OF NUCLEAR ENERGY, 2015, 85 : 753 - 762