Improved Ensemble Learning for Wind Turbine Main Bearing Fault Diagnosis

Improved Ensemble Learning for Wind Turbine Main Bearing Fault Diagnosis

The goal of this paper is to develop, implement, and validate a methodology for wind turbines’ main bearing fault prediction based on an ensemble of an artificial neural network (normality model designed at turbine level) and an isolation forest (anomaly detection model designed at wind park level)...

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Bibliographic Details
Main Authors: Mattia Beretta, Yolanda Vidal, Jose Sepulveda, Olga Porro, Jordi Cusidó
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
fault prognosis
WT
main bearing
normality model
real SCADA data
Online Access:https://www.mdpi.com/2076-3417/11/16/7523

Internet

https://www.mdpi.com/2076-3417/11/16/7523

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