Remaining Useful Life Estimation Framework for the Main Bearing of Wind Turbines Operating in Real Time
Januário Leal de Moraes Vieira,
Felipe Costa Farias,
Alvaro Antonio Villa Ochoa,
Frederico Duarte de Menezes,
Alexandre Carlos Araújo da Costa,
José Ângelo Peixoto da Costa,
Gustavo de Novaes Pires Leite,
Olga de Castro Vilela,
Marrison Gabriel Guedes de Souza,
Paula Suemy Arruda Michima
Affiliations
Januário Leal de Moraes Vieira
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Felipe Costa Farias
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Alvaro Antonio Villa Ochoa
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Frederico Duarte de Menezes
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Alexandre Carlos Araújo da Costa
Department of Mechanical Engineering, Federal University of Pernambuco, Cidade Universitaria, 1235, Recife 50670-901, Brazil
José Ângelo Peixoto da Costa
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Gustavo de Novaes Pires Leite
Department of Higher Education Courses (DACS), Federal Institute of Education, Science and Technology of Pernambuco, Av. Prof Luiz Freire, 500, Recife 50740-545, Brazil
Olga de Castro Vilela
Centro de Energias Renováveis (CER), Universidade Federal de Pernambuco, Cidade Universitaria, 1235, Recife 50670-901, Brazil
Marrison Gabriel Guedes de Souza
NEOG—New Energy Options Geração de Energia, Guamaré 59598-000, Brazil
Paula Suemy Arruda Michima
Department of Mechanical Engineering, Federal University of Pernambuco, Cidade Universitaria, 1235, Recife 50670-901, Brazil
The prognosis of wind turbine failures in real operating conditions is a significant gap in the academic literature and is essential for achieving viable performance parameters for the operation and maintenance of these machines, especially those located offshore. This paper presents a framework for estimating the remaining useful life (RUL) of the main bearing using regression models fed operational data (temperature, wind speed, and the active power of the network) collected by a supervisory control and data acquisition (SCADA) system. The framework begins with a careful data filtering process, followed by creating a degradation profile based on identifying the behavior of temperature time series. It also uses a cross-validation strategy to mitigate data scarcity and increase model robustness by combining subsets of data from different available turbines. Support vector, gradient boosting, random forest, and extra trees models were created, which, in the tests, showed an average of 20 days in estimating the remaining useful life and presented mean absolute error (MAE) values of 0.047 and mean squared errors (MSE) of 0.012. As its main contributions, this work proposes (i) a robust and effective regression modeling method for estimating RUL based on temperature and (ii) an approach for dealing with a lack of data, a common problem in wind turbine operation. The results demonstrate the potential of using these forecasts to support the decision making of the teams responsible for operating and maintaining wind farms.