Expert knowledge modelling software design based on Signed Directed Graph with the application for PWR fault diagnosis

被引：1
|
作者：
Ma, Zhanguo [1 ,2 ]
Deng, Shiguang [3 ]
Zhou, Zhuoran [2 ]
Ai, Xin [2 ]
Zhang, Jing [3 ]
Liu, Yongkuo [2 ]
Peng, Minjun [2 ]
Cui, Jing [1 ]
机构：
[1] Harbin Univ Sci & Technol, Sch Automat, Harbin 150080, Peoples R China
[2] Harbin Engn Univ, Coll Nucl Sci & Technol, Fundamental Sci Nucl Safety & Simulat Technol Lab, Harbin 150001, Heilongjiang, Peoples R China
[3] CNNC China Nucl Power Engn Co Ltd, Beijing 100840, Peoples R China
来源：
ANNALS OF NUCLEAR ENERGY | 2024年 / 196卷
关键词：
Signed directed graph; Fault detection and diagnosis; Expert knowledge models; SDG; SAFETY;
D O I：
10.1016/j.anucene.2023.110206
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：
Online monitoring and Fault Diagnosis and Detection (FDD) can help the operator to enhance the situation awareness. The Signed Directed Graph (SDG) has the significant advantages that SDG-based FDD not only infers the incipient faults and reveals fault propagation paths but also comprehensively explains causes of failure. In this study, an expert knowledge modelling software is designed and developed based on SDG method. Firstly, the SDG-based process monitoring and FDD algorithms are derived by coupling the threshold method and the quality trend analysis method. Secondly, the expert knowledge modelling software is designed and developed not only considering the convenience of the engineer but also the effectiveness of the SDG-based algorithms. Finally, a Pressurized Water Reactor (PWR) is applied to demonstrate the SDG modelling and verify the SDG models. The case study demonstrates that the developed expert knowledge modelling software can effectively diagnose the incipient faults and infer variable impact as the fault propagation paths
引用
收藏
页数：11
相关论文
共 50 条
  • [41] Fault Diagnosis of Nuclear Power Plant Based on Simplified Signed Directed Graph with Principal Component Analysis and Support Vector Machine
    Ma Xin
    Wu Jiao
    Li Da-zi
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 3082 - 3087
  • [42] Fault Propagation Analysis of IGBT Fault in CRH5 Traction System Based on Signed Directed Graph
    Xu, Xi
    Lu, Ningyun
    Yong, Jiaqi
    Jiang, Bin
    2016 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHENGDU), 2016,
  • [43] Application of fault diagnosis expert system based on simulation
    Song, Xin-Min
    Long, Yang-Xi
    Jia, Zhi-Jun
    Wang, Xue-Ming
    Xitong Fangzhen Xuebao / Journal of System Simulation, 2006, 18 (04): : 1038 - 1040
  • [44] Model and Expert Knowledge Based Fault Diagnosis for a Heat Exchanger
    Treyer, Daniel
    Zogg, David
    2013 2ND INTERNATIONAL CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL), 2013, : 680 - 685
  • [45] A Fault Identification Method in Distillation Process Based on Dynamic Mechanism Analysis and Signed Directed Graph
    Tian, Wende
    Zhang, Shifa
    Cui, Zhe
    Liu, Zijian
    Wang, Shaochen
    Zhao, Ya
    Zou, Hao
    PROCESSES, 2021, 9 (02) : 1 - 17
  • [46] DIRECTED GRAPH BASED REPRESENTATION FOR SOFTWARE SYSTEM-DESIGN
    VARADHARAJAN, V
    BAKER, KD
    SOFTWARE ENGINEERING JOURNAL, 1987, 2 (01): : 21 - 28
  • [47] Knowledge Graph Construction for Secondary Equipment Fault Diagnosis Based on Graph Attention
    Mu, Juntao
    Song, Shengcheng
    Ye, Lijuan
    Shi, Yulin
    Zhou, Wei
    Chen, Bin
    Yang, Yongkang
    Proceedings - 2024 International Conference on Artificial Intelligence and Power Systems, AIPS 2024, 2024, : 24 - 27
  • [48] Fault diagnosis of clutch engagement process in heavy off-road vehicle equipped with AMT system based on signed directed graph
    Liu, Hai-Ou, 1600, Beijing Institute of Technology (34):
  • [49] Fault Diagnosis and Prediction for Space Vehicles Based on Improved Directed Graph
    Nan, Yi
    Yi, Guoxing
    Kang, Zhiyu
    INTERNATIONAL CONFERENCE ON ELECTRICAL AND CONTROL ENGINEERING (ICECE 2015), 2015, : 605 - 614
  • [50] Application of the Directed Graph Method in the Knowledge Analysis of Clothing Pattern Design
    He, Chao-Jun
    Ying, Bo-An
    Wang, Xiao-Feng
    Qi, Jing
    TEXTILE BIOENGINEERING AND INFORMATICS SYMPOSIUM (TBIS) PROCEEDINGS, 2020, 2020, : 215 - 223
12345