Supervisory Control and Data Acquisition for Fault Diagnosis of Wind Turbines via Deep Transfer Learning

The installed wind power capacity is growing worldwide. Remote condition monitoring of wind turbines is employed to achieve higher up-times and lower maintenance costs. Machine learning approaches can be used for detecting developing faults in wind turbines in their earlier occurrence. However, trai...

Full description

Bibliographic Details
Main Authors:	Castaldi, P. (Author), Farsoni, S. (Author), Simani, S. (Author)
Format:	Article
Language:	English
Published:	MDPI 2023
Subjects:	Condition based maintenance condition monitoring Condition monitoring Convolutional neural network convolutional neural networks Convolutional neural networks Data acquisition Deep learning Detection models Diagnostic diagnostics fault detection Fault detection Faults detection Faults diagnosis Knowledge management Learning systems Remote condition monitoring supervisory control and data acquisition Supervisory control and data acquisition transfer learning Transfer learning Up-time Wind power Wind power capacity wind turbines Wind turbines
Online Access:	View Fulltext in Publisher

Internet

View Fulltext in Publisher

Supervisory Control and Data Acquisition for Fault Diagnosis of Wind Turbines via Deep Transfer Learning

Internet

Similar Items