2013-04-292013-04-292013-02-27ROCHA, Erick Melo. Metodologia baseada em sistema fuzzy intervalar do tipo-2 para detecção e identificação de faltas de incipientes em motores de indução. Orientador: Walter Barra Júnior. 2013. 76 f. Dissertação (Mestrado em Engenharia Elétrica.) - Instituto de Tecnologia, Universidade Federal do Pará, Belém, 2013. Disponível em: http://repositorio.ufpa.br/jspui/handle/2011/3754. Acesso em:.https://repositorio.ufpa.br/handle/2011/3754Since the incorporation of automation in the production processes, aiming at order to improve productivity and quality of products and services, researches on more efficient methodologies for fault diagnosis became more intensive. Such techniques allow the early detection of faults, before then lead to failures. This work investigates techniques for detection and diagnosis of faults and its application to induction motors, limiting their study to two situations, namely: system free of faults and system under incipient partial short-circuit in the coils the stator winding. For faults detection, parametric analysis of fist order ARX (autoregressive with exogenous input) were applied. The parameters of identified ARX modes, which bring information about the dynamics of the dominant system, are recursively obtained by the techniques of recursive least squares (RLS). In order to evaluate the capability for early fault detection, a type-2 interval fuzzy system was developed. This kind of fuzzy system has capability to capture a larger set of uncertainties than conventional (type-1) fuzzy systems. The footprint of uncertainty (FOU), characteristic of type-2 fuzzy system, is a way to accounts for uncertainties coming from noise and numerical errors from the process of parameter estimation. The ARX model parameters are the inputs to the supervisor system. Genetic algorithms (GA’s) were used for optimization of SIF interval type-2, aiming at to reduce the diagnostic error. The results obtained in tests of computer simulation show the effectiveness of the proposed methodology.porAcesso AbertoSistema Fuzzy intervalar do tipo-2Diagnóstico de faltasAlgoritmos genéticosIdentificação paramétricaFault diagnosisParametric identificationInterval type-2 system fuzzyGenetics algorithmsDissertaçãoCNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::ELETRONICA INDUSTRIAL, SISTEMAS E CONTROLES ELETRONICOS::AUTOMACAO ELETRONICA DE PROCESSOS ELETRICOS E INDUSTRIAIS