Identification of pressure control system dynamics in BWR plant by multivariate autoregressive modeling technique.

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概要

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• Dynamics of a BWR plant pressure control system were studied using stationary noise data for development of a plant diagnosis technique. A multivariate autoregressive (AR) modeling technique has been widely used for similar purposes. However, this cannot be applied to the pressure control system, since the system contains highly coherent signals and its partial transfer mechanism possesses a fast time constant. The present study solved these difficulties by introducing an associate matrix, which described a priori rela-tionships between objective signals, into the conventional AR model.<BR>Using this modified AR model, internal (open loop) and closed loop transfer functions were identified. Their validity was confirmed by comparing with actual transient test data. These results show the effectiveness of noise data for evaluating not only partial component dynamics in the pressure control system but also whole system dynamics, such as a plant stability.

• 一般社団法人 日本原子力学会の論文

著者

• KANEMOTO Shigeru

  Nippon Atomic Industry Group Co., Ltd.

• ANDOH Yasumasa

  Nippon Atomic Industry Group Co., Ltd.

• YAMAMOTO Fumiaki

  Toshiba Corp.

• NUNOME Kikuo

  Chiubu Electric Power Co., Inc.

• KITAMOTO Koichi

  Chiubu Electric Power Co., Inc.

関連論文

• Development of BWR plant diagnosis systm using noise analysis.
• Estimation of fuel channel inlet flow rate by noise analysis.
• Identification of BWR Feedwater Control System using Autoregressive Integrated Model
• Multivariate analyses for neutron noise source identification in BWR plant.
• Identification of pressure control system dynamics in BWR plant by multivariate autoregressive modeling technique.

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