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Characterizing and Computing HBG-PCs for Hybrid Systems Fault Diagnosis

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Advances in Artificial Intelligence (CAEPIA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9422))

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Abstract

Possible Conflicts (PCs) are those minimally redundant subsystems, computed offline, that can be used for consistency-based diagnosis of physical systems. In this work we characterize Possible Conflicts for hybrid systems diagnosis in the Hybrid Bond Graph modelling framework, introducing the notion of HBG-PCs. We provide a method to compute the complete set of HBG-PCs before causality is assigned in the model, removing a previous assumption that the system model should have a valid causal assignment when every switching junction was set to on. We call this new concept Structural HBG-PC. We illustrate these issues with an prototypical example and discuss our contributions against other proposals in the literature.

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Notes

  1. 1.

    The Artificial Intelligence approach to model-based diagnosis it is usually knwon as DX, while the Control Theory approach to the same problem is usually known as FDI.

  2. 2.

    Exceptionally some degenerated subsystems can appear, but they had no interest for diagnosis purposes.

  3. 3.

    Otherwise there would be parts of the system that will be never used, or there is no need for such sw in the model.

  4. 4.

    It is straightforward propagating from sensor/sources an traversing non-parametric junctions.

  5. 5.

    http://www.infor.uva.es/~belar/HBGPCS_results/results.pdf has a complete description of the systems and the results.

References

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Acknowledgments

This work has been supported by Spanish MINECO under DPI2013-45414-R grant.

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Authors and Affiliations

  1. Departamento de Informática, Universidad de Valladolid, Valladolid, Spain

    Belarmino Pulido, Carlos Alonso-González, Anibal Bregon & Alberto Hernández

Authors
  1. Belarmino Pulido
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  2. Carlos Alonso-González
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  3. Anibal Bregon
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  4. Alberto Hernández
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Corresponding author

Correspondence to Belarmino Pulido .

Editor information

Editors and Affiliations

  1. University of Castilla-La Mancha, Albacete, Spain

    José M. Puerta

  2. University of Castilla-La Mancha, Albacete, Spain

    José A. Gámez

  3. University of Cadiz, Cadiz, Spain

    Bernabe Dorronsoro

  4. Public University of Navarre, Pamplona, Spain

    Edurne Barrenechea

  5. Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso

  6. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Bruno Baruque

  7. Public University of Navarre, Pamplona, Spain

    Mikel Galar

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Pulido, B., Alonso-González, C., Bregon, A., Hernández, A. (2015). Characterizing and Computing HBG-PCs for Hybrid Systems Fault Diagnosis. In: Puerta, J., et al. Advances in Artificial Intelligence. CAEPIA 2015. Lecture Notes in Computer Science(), vol 9422. Springer, Cham. https://doi.org/10.1007/978-3-319-24598-0_11

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  • DOI: https://doi.org/10.1007/978-3-319-24598-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24597-3

  • Online ISBN: 978-3-319-24598-0

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