masterThesis
Utilização de redes neurais artificiais para detecção e diagnóstico de falhas
Fecha
2011-06-21Registro en:
REBOUÇAS, Diogo Leite. Utilização de redes neurais artificiais para detecção e diagnóstico de falhas. 2011. 93 f. Dissertação (Mestrado em Automação e Sistemas; Engenharia de Computação; Telecomunicações) - Universidade Federal do Rio Grande do Norte, Natal, 2011.
Autor
Rebouças, Diogo Leite
Resumen
In a real process, all used resources, whether physical or developed in software, are
subject to interruptions or operational commitments. However, in situations in which
operate critical systems, any kind of problem may bring big consequences. Knowing
this, this paper aims to develop a system capable to detect the presence and indicate the
types of failures that may occur in a process. For implementing and testing the proposed
methodology, a coupled tank system was used as a study model case. The system should
be developed to generate a set of signals that notify the process operator and that may
be post-processed, enabling changes in control strategy or control parameters. Due to
the damage risks involved with sensors, actuators and amplifiers of the real plant, the
data set of the faults will be computationally generated and the results collected from
numerical simulations of the process model. The system will be composed by structures
with Artificial Neural Networks, trained in offline mode using Matlab®