1-6 of 6
Chenyu Liu
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles

Condition Monitoring of Wind Turbine Drivetrain Bearings

Konstantinos Gryllias, Junyu Qi, Alexandre Mauricio, Chenyu Liu
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. July 2024, 146(7): 071001.
Paper No: GTP-22-1001
https://doi.org/10.1115/1.4064366
Published Online: February 8, 2024
View Article titled, Condition Monitoring of Wind Turbine Drivetrain Bearings
Open the PDF for Condition Monitoring of Wind Turbine Drivetrain Bearings in another window
Topics: Bearings, Condition monitoring, Signals, Wind turbines, Vibration
Journal Articles

Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description

Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. September 2023, 145(9): 091009.
Paper No: GTP-23-1186
https://doi.org/10.1115/1.4062768
Published Online: July 27, 2023
View Article titled, Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description
Open the PDF for Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description in another window
Topics: Condition monitoring, Wind turbines, Artificial neural networks
Proceedings Papers

Semi-Supervised CNN-Based SVDD Anomaly Detection for Condition Monitoring of Wind Turbines

Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias
Proc. ASME. IOWTC2022, ASME 2022 4th International Offshore Wind Technical Conference, V001T01A019, December 7–8, 2022
Publisher: American Society of Mechanical Engineers
Paper No: IOWTC2022-98704
https://doi.org/10.1115/IOWTC2022-98704
View Paper titled, Semi-Supervised CNN-Based SVDD Anomaly Detection for Condition Monitoring of Wind Turbines
Open the PDF for Semi-Supervised CNN-Based SVDD Anomaly Detection for Condition Monitoring of Wind Turbines in another window
Topics: Condition monitoring, Wind turbines
Proceedings Papers

Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description

Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias
Proc. ASME. GT2022, Volume 11: Wind Energy, V011T38A018, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-82624
https://doi.org/10.1115/GT2022-82624
View Paper titled, Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description
Open the PDF for Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description in another window
Topics: Condition monitoring, Wind turbines
Proceedings Papers

An Improved 2DCNN With Focal Loss Function for Blade Icing Detection of Wind Turbines Under Imbalanced SCADA Data

Dandan Peng, Chenyu Liu, Wim Desmet, Konstantinos Gryllias
Proc. ASME. IOWTC2021, ASME 2021 3rd International Offshore Wind Technical Conference, V001T01A018, February 16–17, 2021
Publisher: American Society of Mechanical Engineers
Paper No: IOWTC2021-3527
https://doi.org/10.1115/IOWTC2021-3527
View Paper titled, An Improved 2DCNN With Focal Loss Function for Blade Icing Detection of Wind Turbines Under Imbalanced SCADA Data
Open the PDF for An Improved 2DCNN With Focal Loss Function for Blade Icing Detection of Wind Turbines Under Imbalanced SCADA Data in another window
Topics: Artificial neural networks, Blades, Wind turbines
Proceedings Papers

Condition Monitoring of Wind Turbine Drivetrain Bearings

Konstantinos Gryllias, Junyu Qi, Alexandre Mauricio, Chenyu Liu
Proc. ASME. IOWTC2019, ASME 2019 2nd International Offshore Wind Technical Conference, V001T01A033, November 3–6, 2019
Publisher: American Society of Mechanical Engineers
Paper No: IOWTC2019-7603
https://doi.org/10.1115/IOWTC2019-7603
View Paper titled, Condition Monitoring of Wind Turbine Drivetrain Bearings
Open the PDF for Condition Monitoring of Wind Turbine Drivetrain Bearings in another window
Topics: Bearings, Condition monitoring, Wind turbines, Ocean engineering, Vibration, Wind, Floating wind turbines, Maintenance, Offshore wind turbines, Wind energy