Resumen

HURTADO-CORTES, Luini Leonardo; VILLARREAL-LOPEZ, Edwin  y  VILLARREAL-LOPEZ, Luís. Fault detection and diagnosis through artificial intelligence techniques, a state of art. Dyna rev.fac.nac.minas [online]. 2016, vol.83, n.199, pp.19-28. ISSN 0012-7353.  https://doi.org/10.15446/dyna.v83n199.55612.

This article presents the current state of artificial intelligence techniques and their application to the field of fault detection and diagnosis, in dynamical systems. Initially, a brief description of what is considered a mechanism for fault detection and diagnosis, and current approaches to the study and implementation of such mechanisms are explained. Subsequently, the most important results of the various artificial intelligence techniques applied to the fault detection and diagnosis are presented. Finally, a comparative analysis based on the desired characteristics of the mechanisms of fault detection and diagnosis is presented. The article concludes by mentioning the benefits of the classification of techniques presented and the listing possible pathways to where you should go research in this field.

Palabras clave : fault detection and diagnosis; artificial neural networks; fuzzy logic systems; neuro-fuzzy systems and immune systems.

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