Investigation on Application of Intelligent Control in SGTR Procedure
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摘要: 核电厂发生蒸汽发生器传热管破裂（SGTR）事故后，操纵员需按相应规程进行操作。但在事故序列处理中，一回路冷却剂的降温、降压效果大多依靠操纵员的运行经验。针对该问题，本文提出一种基于长短期记忆神经网络（LSTM）和自适应比例-积分-微分（PID）的SGTR规程优化方法，并给出了实现流程。利用某1000 MW模拟机开展了SGTR事故模拟实验，基于模拟实验数据对本文方法进行了测试。仿真结果表明，与操纵员人工操作相比，本文提出的智能操作方法具有更好的降温、降压效果，本文方法可为核电厂事故规程的智能化操作提供一种新思路。
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关键词:
- 核电厂 /
- 蒸汽发生器传热管破裂（SGTR） /
- 运行规程优化 /
- 长短期记忆神经网络（LSTM）
Abstract: After the occurrence of steam generator heat transfer tube rupture (SGTR) accident in nuclear power plant, operators shall follow the corresponding procedures. However, in accident sequence processing, the cooling and depressurizing effects of primary circuit coolant mostly depend on the operating experience of the operator. To solve this problem, this paper proposes a SGTR operating procedure optimization method based on LSTM and adaptive proportional-integral-differential (PID), and gives the implementation process. The SGTR accident simulation experiment was carried out by a 1000 MW simulator. Based on the simulation experiment data, the proposed method was tested. Simulation results show that, compared with manual operation, the proposed intelligent operation method has better cooling and depressurization effects. The proposed method can provide a new idea for intelligent operation of accident procedures in nuclear power plants. -
图 3 智能控制模块示意图
x(t)—仿真机中相应阀门的开度值；y'(t)—LSTM模型计算出的温度降低速率或过冷度的预测值；y(t)—仿真机中温度降低速率或过冷度的实际值；y0—温度降低速率或过冷度的设定值；e(t)—y(t)与y0的差值；KP—比例调节系数；KI—积分调节系数；KD—微分调节系数；u(t)—输入到仿真机中的阀门开度指令
Figure 3. Schematic Diagram of Intelligent Control Module
图 4 SGTR规程优化流程图
RMSE—均方根误差
Figure 4. Flow Chart of SGTR Operating Procedure Optimization
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[1] AHN J, LEE S J. Deep learning-based procedure compliance check system for nuclear power plant emergency operation[J]. Nuclear Engineering and Design, 2020, 370: 110868. doi: 10.1016/j.nucengdes.2020.110868 [2] 刘立欣,王喆. 核电厂SGTR规程优化研究[J]. 核动力工程,2022, 43(4): 126-130. [3] 刘海宇,李力,李骜. 基于任务分析的核电厂计算机化运行规程人机界面研究[J]. 核科学与工程,2021, 41(3): 649-656. [4] 沈学泽. 核电厂事故规程信息化系统对操纵员工作负荷的影响研究[D]. 衡阳: 南华大学, 2021. [5] 许余,黄远远,熊立红,等. 基于本体的核电运行规程模型构建方法[J]. 核动力工程,2020, 41(5): 142-145. [6] KIM H, ARIGI A M, KIM J. Development of a diagnostic algorithm for abnormal situations using long short-term memory and variational autoencoder[J]. Annals of Nuclear Energy, 2021, 153: 108077. doi: 10.1016/j.anucene.2020.108077 [7] LEE S, KIM J. Design of computerized operator support system for technical specification monitoring[J]. Annals of Nuclear Energy, 2022, 165: 108661. doi: 10.1016/j.anucene.2021.108661 -
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