Predictive maintenance in LED street lighting controlled with telemanagement system to improve current fault detection procedures using software tools.

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

Resumen

Predicting the lifetime of LED light sources becomes quite challenging because the time to failure is long. The LM-80 and TM-21 methods are the main used by companies to establish the product lifetime. Accurate the RUL prediction can facilitate predictive maintenance. Predictive maintenance allows estimating when a failure will occur. In this context, the maintenance can be planned in advance, eliminating unplanned outage and maximizing the useful life of the equipment. In this work, the LM-80 and TM-21 methods are used for the acquisition and extrapolation of luminous flux data, wich are entered into an algorithm developed from an exponential degradation model. With the result obtained, it is possible to establish actions that allow predictive maintenance in LED street lighting controlled by a remote management system and achieve a longer service life.

Idioma originalInglés
Páginas (desde-hasta)379-386
Número de páginas8
PublicaciónRenewable Energy and Power Quality Journal
Volumen20
DOI
EstadoPublicada - sep. 2022

Nota bibliográfica

Publisher Copyright:
© 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

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