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A Novel Approach to Detect Single and Multiple Faults in Complex Systems Based on Soft Computing Techniques

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Hybrid Artificial Intelligent Systems (HAIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9121))

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Abstract

To ensure complex systems reliability and to extent their life cycle, it is crucial to properly and timely correct eventual faults. In this context, this paper propose an intelligent approach to detect single and multiple faults in complex systems based on soft computing techniques. This approach is based on the combination of fuzzy logic reasoning and Artificial Fish Swarm optimization. The experiments focus on a simulation of the three-tank hydraulic system, a benchmark in the diagnosis domain.

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References

  1. Patton, R., Uppal, F., Lopez-Toribio, C.: Soft computing approaches to fault diagnosis for dynamic systems: a survey. In: 4th IFAC Symposium on Fault Detection supervision and Safety for Technical Processes, pp. 198–211 (2000)

    Google Scholar 

  2. Calado, J., Korbicz, J., Patan, K., Patton, R.J., Da Costa, J.S.: Soft computing approaches to fault diagnosis for dynamic systems. Eur. J. Control 7(2), 248–286 (2001)

    MATH  Google Scholar 

  3. Witczak, M.: Modelling and Estimation Strategies for Fault Diagnosis of Non-linear Systems: from Analytical to Soft Computing Approaches, vol. 354. Springer Science and Business Media, Ottawa (2007)

    Google Scholar 

  4. Chen, J., Patton, R.J.: Robust Model-based Fault Diagnosis for Dynamic Systems, Incorporated. Springer Publishing Company, New York (2012)

    Google Scholar 

  5. Yager, R.R., Zadeh, L.A.: An Introduction to Fuzzy Logic Applications in Intelligent Systems. Kluwer Academic Publishers, Norwell (1992)

    Book  MATH  Google Scholar 

  6. Pourghasemi, H.R., Pradhan, B., Gokceoglu, C.: Application of fuzzy logic and analytical hierarchy process (ahp) to landslide susceptibility mapping at haraz watershed, iran. Nat. Hazards 63(2), 965–996 (2012)

    Google Scholar 

  7. Berhan, E., Abraham, A.: Hierarchical fuzzy logic system for manuscript evaluation. Middle-East J. Sci. Res. 19(9), 1235–1245 (2014)

    Google Scholar 

  8. Zadeh, L.: Computing with Words: Principal Concepts and Ideas, Incorporated. Springer Publishing Company, Berlin (2014)

    Google Scholar 

  9. Li, X.I., Shao, Z.J., Qian, J.X.: An optimizing method based on autonomous animats: fish-swarm algorithm. Syst. Eng. Theory Pract. 22(11), 32–38 (2003)

    Google Scholar 

  10. Neshat, M., Sepidnam, G., Sargolzaei, M., Toosi, A.N.: Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artifi. Intell. Rev. 42(4), 965–997 (2014)

    Google Scholar 

  11. Neshat, M., Adeli, A., Sepidnam, G., Sargolzaei, M., Toosi, A.N.: A review of artificial fish swarm optimization methods and applications. Int. J. Smart Sens. Intell. Syst. 5(1), 107–148 (2012)

    Google Scholar 

  12. Hofling, T., Isermann, R.: Fault detection based on adaptive parity equations and single-parameter tracking. Control Eng. Pract. 4(10), 1361–1369 (1996)

    Google Scholar 

  13. Basseville, M.: Segmentation de signaux: introduction. Traitement du Sig. 9(1), 115–119 (1992)

    Google Scholar 

  14. Frank, P., Kiupel, N.: Fuzzy supervision and application to lean production. Int. Syst. Sci. 24(10), 1935–1944 (1993)

    Google Scholar 

  15. Fliss, I., Tagina, M.: Multiple faults model-based detection and localisation in complex systems. J. Decis. Syst. 20(1), 7–31 (2011)

    Google Scholar 

  16. Fliss, I., Tagina, M.: Hybrid intelligent approach to diagnose multiple faults in complex systems, In: 14th International Conference on Hybrid Intelligent Systems (HIS 2014), December 14–16, 2014, Kuwait (2014)

    Google Scholar 

  17. Janati-Idrissi, H., Adrot, O., Ragot, J.: Residual generation for uncertain models. In: 40th Conference on Decision and control, Orlando, Etats-Unis (2001)

    Google Scholar 

  18. Heim, B.: Approche Ensembliste et par Logique Floue pour le diagnostic causal de procedes de raffinage. Application un pilote FCC. Ph.D. thesis, Institut Polytechnique de Grenoble (2003)

    Google Scholar 

  19. Albusac, J., Castro-Schez, J., Vallejo, D., Jimenez-Linares, L.: Learning maximal structure rules with pruning based on distances between fuzzy sets. In: Proceedings of the Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU, vol. 8, pp. 441–447 (2008)

    Google Scholar 

  20. AmiraGmbH: Amira-DTS200 Laboratory Setup Three Tank System, Bismarckstra. D-47057 Duisburg, Germany (2002)

    Google Scholar 

  21. Dauphin-Tanguy, G.: Les Bond Graph. Hermes Sciences Publications, Paris (2000)

    Google Scholar 

  22. Borutzky, W.: Bond Graph Modelling of Engineering Systems. Springer, New York (2011)

    Book  MATH  Google Scholar 

  23. Gentil, S.: Supervision des Procedes Complexes. Hermes Science Publication, Paris (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. COSMOS Laboratory, National School of Computer Sciences, Manouba University, Manouba, Tunisia

    Imtiez Fliss & Moncef Tagina

Authors
  1. Imtiez Fliss
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  2. Moncef Tagina
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Corresponding author

Correspondence to Imtiez Fliss .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Enrique Onieva

  2. University of Deusto, Bilbao, Spain

    Igor Santos

  3. University of Deusto, Bilbao, Spain

    Eneko Osaba

  4. Universidad de Salamanca, Salamanca, Spain

    Héctor Quintián

  5. Universidad de Salamanca, Salamanca, Spain

    Emilio Corchado

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Fliss, I., Tagina, M. (2015). A Novel Approach to Detect Single and Multiple Faults in Complex Systems Based on Soft Computing Techniques. In: Onieva, E., Santos, I., Osaba, E., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2015. Lecture Notes in Computer Science(), vol 9121. Springer, Cham. https://doi.org/10.1007/978-3-319-19644-2_28

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  • DOI: https://doi.org/10.1007/978-3-319-19644-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19643-5

  • Online ISBN: 978-3-319-19644-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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