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Directed hypergraph observers-based qualitative fault monitoring tasks

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
To create a precise model structure and perform fault monitoring algorithms for a wide range of complex systems along with dynamic behavioural characteristics, the causal graph-based methods were considered herein. In this paper, a new scheme was devised based on fast fault detection mechanism relying on the Directed Hypergraph Observer model. The performance of the suggested pattern is illustrated by a case study including systems with single energy. Noting that the modern methods possess a large range of applications for the reliability and energy effectiveness analysis related to multi-energy systems. The Directed Hypergraph model architecture was exploited to generate the diagnostic condition based on a graphical observer.
Czasopismo
Rocznik
Strony
67--76
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
autor
  • LISI Laboratory, INSAT/Carthage University, Tunisia
  • Macs Laboratory, University of Gabes, Tunisia
autor
  • LISI Laboratory, INSAT/Carthage University, Tunisia
Bibliografia
  • 1. Isermann R. Fault-diagnosis systems: an introduction from fault detection to fault tolerance. Springer Science & Business Media, 2005.
  • 2. Blanke M, Kinnaert M, Lunze J. Diagnosis and fault-tolerant control. Berlin: Springer, 2006.
  • 3. Serra R, Zanarini G. Complex systems and cognitive processes. Springer Science & Business Media, 2013.
  • 4. Patton RJ, Frank PM, Clark RN. Issues of fault diagnosis for dynamic systems. Springer Science & Business Media, 2013.
  • 5. Samantaray AK, Bouamama BO. Model-based process supervision: a bond graph approach. Springer Science & Business Media, 2008.
  • 6. Borutzky W. Bond graph model-based fault diagnosis of hybrid systems. Cham: Springer International Publishing, 2015.
  • 7. BERGE, Claude. Graphs and hypergraphs. 1973.
  • 8. Klein D, Manning CD. Parsing and hypergraphs. In : New developments in parsing technology. Springer, Dordrecht. 2004 :351-372.
  • 9. Ausiello G, Italiano, GF, Laura L, et al. Structure theorems for optimum hyperpaths in directed hypergraphs. In: International Symposium on Combinatorial Optimization. Springer, Berlin, Heidelberg. 2012:1-14.
  • 10. Gallo G, Longo G, Pallottino S, et al. Directed hypergraphs and applications. Discrete applied mathematics. 1993:42(2-3):177-201.
  • 11. Klamt S, Haus Utz-Uwe. Hypergraphs and cellular networks. PLoS Comput Biol, 2009; 5(5): e1000385.
  • 12. Gazdík I. Modelling systems by hypergraphs. Kybernetes. 2006.
  • 13. Adamski M, Tkacz J. Formal reasoning in logic design of reconfigurable controllers. IFAC Proceedings Volumes. 2012; 45(7):1-6.
  • 14. Khalil W, Merzouki R, Ould-Bouamama B. Hypergraph models for system of systems supervision design. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans. 2012; 42(4):1005-1012. https://doi.org/10.1109/TSMCA.2012.2183350.
  • 15. Haffaf H. Hypergraph for system of systems modeling. Networking and Advanced Systems. 2015: 38.
  • 16. Abdesselam I, Haffaf H. Hypergraph reconfigurability analysis. IERI Procedia. 2014; 6:22-32.
  • 17. Kotulski L, Sędziwy A, Strug B. Heterogeneous graph grammars synchronization in CAD systems supported by hypergraph representations of buildings. Expert systems with applications. 2014; 41(4):990-998. https://doi.org/10.1016/j.eswa.2013.07.043.
  • 18. Habel A, Kreowski HJ. Some structural aspects of hypergraph languages generated by hyperedge replacement. Annual Symposium on Theoretical Aspects of Computer Science. Springer, Berlin, Heidelberg, 1987:207-219.
  • 19. Minas M. Concepts and realization of a diagram editor generator based on hypergraph transformation. Science of Computer Programming. 2002;44(2): 157-180.
  • 20. Gomand J. Analyse de systèmes multi-actionneurs parallèles par une approche graphique causaleapplication a un processus électromécanique de positionnement rapide. 2008. Thèse de doctorat. Arts et Métiers Paris Tech.
  • 21. Borutzky W. Bond graph model-based fault diagnosis of hybrid systems. Cham: Springer International Publishing, 2015.
  • 22. Saoudi G, Harabi R, Abdelkrim MN. Robust fault detection based on bond graph UIO observer. International Journal of Digital Signals and Smart Systems. 2017;1(4):302-322.
  • 23. Ding SX. Advanced methods for fault diagnosis and fault-tolerant control. Springer Berlin Heidelberg. 2021.
  • 24. Wu Y, Zhao D, Liu S, Li, Y. Fault detection for linear discrete time-varying systems with multiplicative noise based on parity space method. ISA transactions. 2021. https://doi.org/10.1016/j.isatra.2021.04.018.
  • 25. Pan J, He W, Shi Y, Hou R, Zhu H. Uncertainty analysis based on non-parametric statistical modelling method for photovoltaic array output and its application in fault diagnosis. Solar Energy. 2021;225, 831-841.
  • 26. Vijay P, Tadé MO, Shao Z. Adaptive observer based approach for the fault diagnosis in solid oxide fuel cells. Journal of Process Control. 2019; 84, 101-114.
  • 27. Atitallah M, El Harabi R, Abdelkrim MN. Unknown input Hamiltonian observers-based fault detection and estimation. Systems, Automation, and Control. 2019: 177-196.
  • 28. Aboub A, El Harabi R, Abdelkrim MN. Causal ordering graph based observers for generating redundant relations. 17th International MultiConference on Systems, Signals & Devices (SSD). IEEE, 2020:1080-1085.
  • 29. Garai D, El Harabi R, Bacha F. A comparative study of Graphical tools for the Fault Monitoring using HBG and DBH Formalisms. 18th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE. 2021:124-130.
  • 30. Garai D, El Harabi R, Bacha F. Hamiltonian Bond Graph formalism for generating energetic redundant relations. 17th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE. 2020:1063-1068.
  • 31. Merahi F, Bouamama BO, Mekhilef S. Bond graph modeling, design and experimental validation of a photovoltaic/fuel cell/electrolyzer/battery hybrid power system. International Journal of Hydrogen Energy. 2021;46(47):24011-24027. https://doi.org/10.1016/j.ijhydene.2021.05.016.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-93b4c59c-012e-46ee-bddc-f6055d1e51f8
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