Graph of a Process-A New Tool for Finding Model Structures in a Model-Based Diagnosis

被引:17
|
作者
Sztyber, Anna [1 ]
Ostasz, Andrzej [2 ]
Koscielny, Jan M. [1 ]
机构
[1] Warsaw Univ Technol, Inst Automat Control & Robot, Faulty Mechatron, PL-02525 Warsaw, Poland
[2] GE Oil & Gas Warsaw, PL-00113 Warsaw, Poland
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2015年 / 45卷 / 07期
关键词
Causal graphs; fault diagnosis; model structure (MS); qualitative modeling; redundancy; SIGNED DIRECTED GRAPH; DIAGNOSABILITY ANALYSIS; FAULT-DIAGNOSIS; SYSTEM FAILURES; BOND GRAPHS; ALGORITHM; FRAMEWORK;
D O I
10.1109/TSMC.2014.2384000
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, graph of a process (GP) is introduced as a new formalization of causal graph useful in fault diagnosis. Faults are directly incorporated into the model. In this paper, we propose the concept of model structure (MS), which can be used for building fuzzy and neural models for fault detection. Algorithms for finding all MSs and methods for determining faults-symptoms relation are developed. This method is applicable to the design of model-based diagnostic systems, when only basic knowledge of the process to be diagnosed is available. No mathematical model is needed. This paper shows that GP can be constructed on the basis of process diagrams and expert knowledge. Models for fault detection can be built automatically from process measurements. Ideas are explained on a three-tank system example. In the last section, our proposed method is compared in detail with other existing approaches using qualitative models.
引用
收藏
页码:1004 / 1017
页数:14
相关论文
共 50 条
  • [1] Model-based fault diagnosis methods for systems with stochastic process-A survey
    Zhao, Zhen
    Liu, Peter Xiaoping
    Gao, Jinfeng
    NEUROCOMPUTING, 2022, 513 : 137 - 152
  • [2] Model-Based Process Diagnosis: Bond Graph and Signed Directed Graph Tools
    Smaili, Rahma
    El Harabi, Rafika
    Abdelkrim, Mohamed Naceur
    2013 INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT), 2013, : 782 - 787
  • [3] An efficient algorithm for finding minimal overconstrained subsystems for model-based diagnosis
    Krysander, Mattias
    Aslund, Jan
    Nyberg, Mattias
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2008, 38 (01): : 197 - 206
  • [4] Model partitioning for model-based diagnosis
    Katsillis, G
    Chantler, MJ
    (SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3, 1998, : 845 - 850
  • [5] Immune Model-based Fault Diagnosis
    Wang Chu-Jiao
    Xia Shi-Xiong
    2008 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND INFORMATION TECHNOLOGY, PROCEEDINGS, 2008, : 685 - 688
  • [6] Critical observations in model-based diagnosis
    Christopher, Cody James
    Grastien, Alban
    ARTIFICIAL INTELLIGENCE, 2024, 331
  • [7] Optimization problems in model-based diagnosis
    Gertler, J
    Hu, YT
    CONTROL APPLICATIONS OF OPTIMISATION 2003, 2003, : 1 - 8
  • [8] Model-based fault diagnosis and prognosis of dynamic systems: a review
    Ekanayake, Thushara
    Dewasurendra, Devapriya
    Abeyratne, Sunil
    Ma, Lin
    Yarlagadda, Prasad
    DIGITAL MANUFACTURING TRANSFORMING INDUSTRY TOWARDS SUSTAINABLE GROWTH, 2019, 30 : 435 - 442
  • [9] Model-based fault diagnosis in technical processes
    Frank, PM
    Ding, SX
    Marcu, T
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2000, 22 (01) : 57 - 101
  • [10] A model-based fault diagnosis of powered wheelchair
    Itaba, Fumihiro
    Hashimoto, Masafumi
    Takahashi, Kazuhiko
    2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-5, 2007, : 1255 - +