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@Article{EchevarriaCamBecSilSan:2014:FaDiIn,
               author = "Echevarria, L{\'{\i}}dice Camps and Campos Velho, Haroldo Fraga 
                         de and Becceneri, Jose Carlos and Silva Neto, Antonio Jose da and 
                         Santiago, Orestes Llanes",
          affiliation = "CUJAE, Inst Super Politecn Jose Antonio Echeverria, Havana 19390, 
                         Cuba. and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and IPRJ UERJ, 
                         Inst Politecn, Nova Friburgo, RJ, Brazil. and CUJAE, Inst Super 
                         Politecn Jose Antonio Echeverria, Havana 19390, Cuba.",
                title = "The fault diagnosis inverse problem with Ant Colony Optimization 
                         and Ant Colony Optimization with dispersion",
              journal = "Applied Mathematics and Computation",
                 year = "2014",
               volume = "227",
                pages = "687--700",
                month = "Jan.",
                 note = "{Appendix A. Supplementary data} and Supplementary data associated 
                         with this article can be found, in the online version, at 
                         http://dx.doi.org/10.1016/j.amc.2013.11.062.",
             keywords = "Ant Colony Optimization, Fault diagnosis, Industrial systems, 
                         Inverse problem, Robustness, Sensitivity, Structural 
                         detectability, Structural separability.",
             abstract = "This paper is focused on the formulation of fault diagnosis (FDI) 
                         using an inverse problem methodology. The FDI inverse problem is 
                         formulated as an optimization problem which is solved by 
                         bio-inspired algorithms. In this case, the algorithms Ant Colony 
                         Optimization (ACO), and its modified version ACO-d have been 
                         applied. This approach combines results from FDI area for making 
                         an alternative uniqueness analysis of the FDI inverse problem, 
                         which is related with detectability and isolability of faults, 
                         components of the diagnosis. The proposed approach is tested using 
                         simulated data from the Inverted-Pendulum System which is 
                         recognized as a benchmark for control and diagnosis. This work 
                         also studies the influence of ACO and ACO-d parameters in order to 
                         obtain a robust (to external disturbances) and sensitive (to 
                         incipient faults) diagnosis. The results show the suitability of 
                         the approach. They also indicate that parameters values allowing a 
                         greater diversification of the search, yield a better diagnosis. 
                         The ACO-d algorithm enables better diagnosis than ACO.",
                  doi = "10.1016/j.amc.2013.11.062",
                  url = "http://dx.doi.org/10.1016/j.amc.2013.11.062",
                 issn = "0096-3003",
                label = "isi 2014-05 CampsEchevarriaCamBecSilLla:2014:FaDiIn",
             language = "en",
           targetfile = "1-s2.0-S0096300313012319-main.pdf",
                  url = "http://dx.doi.org/10.1016/j.amc.2013.11.062",
        urlaccessdate = "29 nov. 2020"
}


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