Wind turbine gearbox failure monitoring based on SCADA data analysis

Abstract

A model for monitoring the wind turbine gearbox based on Supervisory Control and Data Acquisition (SCADA) data is developed. A deep neural network (DNN) is trained with the data of normal gearboxes to predict its performance. The developed DNN model is next tested with data of the normal and abnormal gearboxes. The abnormal behavior of the gearbox can be detected by the statistical process control charts via the fitting error. The capacity of the monitoring model for detecting the abnormal behavior of gearbox is validated by two gearbox failure cases.