An Association Rule Mining-Based Method for Revealing the Impact of Operational Sequence on Nuclear Power Plants Operating

IF 1 4区工程技术 Q3 NUCLEAR SCIENCE & TECHNOLOGY

Science and Technology of Nuclear Installations Pub Date : 2024-03-25 DOI:10.1155/2024/6618975

Yuxuan He, Jian Song, Shaoke Shi, Haibo Lian, Jiangyang He, Ren Yu, Tete Liu, Bin Sun, Jiangtao Yuan, Yingbin Hu

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引用次数: 0

Abstract

The operations of the operators are important for nuclear safety, but conventional operating experience feedback and common data-driven methods make it difficult to explicitly find valuable information hidden in these operational sequences that can help the operator to provide advice at the operational level. During the nuclear power plant (NPP) operation, a large amount of historical operating data is accumulated, which records the operational sequences of the operators and the state parameters of equipment. Therefore, this paper proposes the use of association rule techniques to mine the NPP operating data to discover the operational characteristics of operators and reveal their possible impact on the NPP operation. This work helps to improve the operational performance of operators and prevent human-factor events. To this end, the concept of state switching values for describing the operating states of NPPs is proposed to enable the proposed method to be adapted to different practical application scenarios. A sequence segmentation method is proposed to be able to transform historical NPP operating data into a sequence data set for association rule mining. Furthermore, an ensemble algorithm based on sequence pattern mining and sequence rule mining and its postprocessing method are designed. The empirical study was carried out using 20 batches of historical operating data of the cold start-up. A total of 164 original association rules are generated using the proposed method and were analyzed by experts. The recommendations were made for 4 different cases that would improve the operational performance of the operators.

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基于关联规则挖掘的方法揭示运行顺序对核电站运行的影响

操作人员的操作对核安全非常重要，但传统的操作经验反馈和常见的数据驱动方法很难明确找到隐藏在这些操作序列中的有价值信息，从而帮助操作人员在操作层面提供建议。在核电站（NPP）运行过程中，积累了大量的历史运行数据，这些数据记录了操作人员的操作序列和设备的状态参数。因此，本文提出利用关联规则技术挖掘核电站运行数据，以发现操作人员的操作特征，并揭示其对核电站运行可能产生的影响。这项工作有助于提高操作员的操作绩效，防止人为因素事件的发生。为此，提出了用于描述核电站运行状态的状态切换值概念，使所提出的方法能够适应不同的实际应用场景。提出了一种序列分割方法，以便能够将核电厂的历史运行数据转化为序列数据集，用于关联规则挖掘。此外，还设计了一种基于序列模式挖掘和序列规则挖掘的集合算法及其后处理方法。实证研究使用了 20 批冷启动历史运行数据。使用所提出的方法共生成了 164 条原始关联规则，并由专家进行了分析。针对 4 种不同情况提出了建议，以提高操作员的操作性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Science and Technology of Nuclear Installations NUCLEAR SCIENCE & TECHNOLOGY-

CiteScore

2.30

自引率

9.10%

发文量

审稿时长

4-8 weeks

期刊介绍： Science and Technology of Nuclear Installations is an international scientific journal that aims to make available knowledge on issues related to the nuclear industry and to promote development in the area of nuclear sciences and technologies. The endeavor associated with the establishment and the growth of the journal is expected to lend support to the renaissance of nuclear technology in the world and especially in those countries where nuclear programs have not yet been developed.