Resumen:
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[ES] En el presente Trabajo Final de Máster (TFM) se pretende desarrollar un sistema de diagnóstico de un elevador industrial mediante el análisis del ruido. Para ello, se usará un dispositivo autónomo capaz de registrar ...[+]
[ES] En el presente Trabajo Final de Máster (TFM) se pretende desarrollar un sistema de diagnóstico de un elevador industrial mediante el análisis del ruido. Para ello, se usará un dispositivo autónomo capaz de registrar el sonido in situ. Este dispositivo, basado en un micro-ordenador Raspberry-pi, cuenta con un micrófono, un disco duro con capacidad de almacenar registros sonoros durante semanas y conectividad Wifi para la transmisión de datos. Seguidamente, se desarrollará el código del sistema de diagnóstico en lenguaje de programación Python para la evaluación del estado del elevador a partir de las características de sus componentes. Finalmente, se deberán proponer una serie de trabajos futuros que puedan surgir de la base del presente TFM.
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[EN] This document will deal with the study of the feasibility of a predictive maintenance system through noise analysis to carry out the diagnosis of an industrial engine. However, this is not going to be general, but the ...[+]
[EN] This document will deal with the study of the feasibility of a predictive maintenance system through noise analysis to carry out the diagnosis of an industrial engine. However, this is not going to be general, but the predictive maintenance system that is going to be developed is going to be destined for an automotive production plant located at Calle La Granja, 16 (Pol Ind Rey Juan Carlos I, 46440 Almussafes called "SAS Interior modules, a Faurecia Company" whose activity will be described later.
In this way, prior to the diagnosis system itself, a complete study of the activity of the industrial plant will be carried out, trying to elucidate which are the most suitable machines and with the greatest need for a predictive maintenance system with the characteristics that are described have been set out, at the same time that said diagnostic system will be adapted so its incorporation into the maintenance routine is viable and compatible with the activity of the plant and the specific use of the machinery, so the effectiveness of the predictive maintenance system will be optimal.
Thus, the necessary equipment will then be installed in the engines or systems of the production plant considered critical to carry out said diagnosis which will allow elucidate whether the study on its feasibility is conclusive or not. This will be done by analyzing the samples taken using that equipment, which will themselves be recordings of the noise from the engine or system.
Subsequently, and after having analyzed the samples that are considered necessary, the conclusions obtained from the study will be made, explaining in them the favorable and unfavorable features of the project that will conclude whether the predictive maintenance system by noise analysis studied is viable or not for the circumstances contemplated.
In addition, the budget and the specifications associated to the project will be included.
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