Proposta de dissertação do MEI
Título: Predicitive maintenance of electric motors
Proponente(s): João Moura Pires e Carlos Damásio
Créditos: 42 ECTS
Área científica: Decision Support and Artificial Intelligence
Início preferencial: Qualquer semestre
URL:
Já estão em curso trabalhos preliminares executados pelo alunos:
Hugo Rações
Breve descrição: This project aims to develop a predictive maintenance platform for electric motors, allowing the industry to have online insights about motors efficiency, fault detection and predictions as well as the motors parameters and a set of other analysis. The use of machine learning techniques, as well as first principles, bring added value to the potencial solutions in monitoring and maintenance in the Big Data era.
Currently the project provides a model for inter-turn short circuit detection (Classification), another one for phase-in-fault-detection (Classification) and a third-one for inter-turn short-circuit severity estimation (Regression). These 3 models were developed in the context of a DI/FCT/UNL Master Thesis during 2016/2017. The next stage of this project involves, enumerating a few examples, (a) developing another model (or models) for detections of another kind of fault and (b) updating the inter-turn short-circuit models with industrial data and more experimental data.
Observações: This project will be developed within ALTRAN Portugal and will include a grant. For mor details about the grant contact jorge.afonso@altran.com