Estudo sobre Modelos de Aprendizado de Máquina para Detecção de Falhas em Turbinas Eólicas
DOI:
https://doi.org/10.5540/03.2023.010.01.0048Palabras clave:
Energia Eólica, Aprendizado de MáquinaResumen
A crescente busca por soluções energéticas renováveis tem trazido destaque para soluções como turbinas eólicas, que são as principais responsáveis pela transformação de energia eólica em elétrica. Assim, o monitoramento, diagnóstico e prognóstico de falhas destas turbinas é fundamental para garantir a produção energética de forma contínua. Estas turbinas são monitorados por sensores e os dados oriundos deste monitoramento podem ser utilizados para criar modelos capazes de detectar estágios iniciais de degradação dos componentes que formam as turbinas, garantindo assim que falhas sejam identificadas rapidamente, reduzindo custos em manutenção. No presente trabalho é apresentada uma breve revisão sobre o assunto, além da aplicação de duas técnicas de aprendizado de máquina em uma base de dados real.
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