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Phenomenological modeling and parametric identification applied to the monitoring of a belt conveyor system in a copper mine

Abstract:

This paper investigates the modeling of a belt conveyor system for use in an automated monitoring system aiming at obtain improved energetic performance and fault diagnosis capability of the system. Firstly, a phenomenological model of the process is discussed, which is based on the laws of mechanics considering various movement opposing forces. The main parameters of the belt conveyor system model were estimated by using a non-recursive least mean square identification techniques. The results of computational studies show a good efficiency of the proposed strategies when applied to a set of data collected in a real world belt conveyor system, located at copper mine in south of Pará state, Brazil.