1-20 of 27
Konstantinos Gryllias
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
Proceedings Papers

SCADA-Based Long-Term Wind Turbine Performance Degradation Analysis Based on Deep Learning Techniques

Dandan Peng, Ludovico Terzi, Wim Desmet, Konstantinos Gryllias
Proc. ASME. GT2024, Volume 13: Heat Transfer: General Interest / Additive Manufacturing Impacts on Heat Transfer; Wind Energy, V013T37A017, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-128709
https://doi.org/10.1115/GT2024-128709
View Paper titled, SCADA-Based Long-Term Wind Turbine Performance Degradation Analysis Based on Deep Learning Techniques
Open the PDF for SCADA-Based Long-Term Wind Turbine Performance Degradation Analysis Based on Deep Learning Techniques in another window
Topics: Condition monitoring, Convolutional neural networks, Deep learning, Wind turbines
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

GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis

Dandan Peng, Wim Desmet, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2024, 146(3): 031009.
Paper No: GTP-23-1254
https://doi.org/10.1115/1.4063578
Published Online: November 6, 2023
View Article titled, GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis
Open the PDF for GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis in another window
Topics: Fault diagnosis, Turbines, Wind, Wind turbines, Artificial neural networks
Proceedings Papers

GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis

Dandan Peng, Wim Desmet, Konstantinos Gryllias
Proc. ASME. GT2023, Volume 14: Wind Energy, V014T37A005, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-102241
https://doi.org/10.1115/GT2023-102241
View Paper titled, GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis
Open the PDF for GLDAN: Global and Local Domain Adaptation Network for Cross-Wind Turbine Fault Diagnosis in another window
Topics: Fault diagnosis, Turbines, Wind, Wind turbines
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

Bearing Diagnostics Using Kurtosis Spectral Correlation Based on Cyclic Modulation Spectrum Estimation

Alexandre Mauricio, Konstantinos Gryllias
Proc. ASME. GT2022, Volume 2: Coal, Biomass, Hydrogen, and Alternative Fuels; Controls, Diagnostics, and Instrumentation; Steam Turbine, V002T05A025, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-83600
https://doi.org/10.1115/GT2022-83600
View Paper titled, Bearing Diagnostics Using Kurtosis Spectral Correlation Based on Cyclic Modulation Spectrum Estimation
Open the PDF for Bearing Diagnostics Using Kurtosis Spectral Correlation Based on Cyclic Modulation Spectrum Estimation in another window
Topics: Bearings, Signals, Transients (Dynamics), Breakdown (Electricity), Damage, Filters, Fourier transforms, Machine components, Maintenance, Noise (Sound)
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
Journal Articles

Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings

Junyu Qi, Alexandre Mauricio, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. April 2022, 144(4): 041019.
Paper No: GTP-20-1604
https://doi.org/10.1115/1.4049797
Published Online: February 21, 2022
View Article titled, Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings
Open the PDF for Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings in another window
Topics: Entropy, Wind turbines, Bearings
Journal Articles

Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions

Alexandre Mauricio, Dustin Helm, Markus Timusk, Jerome Antoni, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. April 2022, 144(4): 041018.
Paper No: GTP-20-1600
https://doi.org/10.1115/1.4049778
Published Online: February 21, 2022
View Article titled, Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions
Open the PDF for Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions in another window
Topics: Machinery, Signals, Stress, Damage, Bearings
Proceedings Papers

Condition Monitoring of Wind Turbines Based on the Scattering Transform of Vibration Data

Junyu Qi, Alexandre Mauricio, Konstantinos Gryllias
Proc. ASME. GT2021, Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture, V001T40A005, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-60280
https://doi.org/10.1115/GT2021-60280
View Paper titled, Condition Monitoring of Wind Turbines Based on the Scattering Transform of Vibration Data
Open the PDF for Condition Monitoring of Wind Turbines Based on the Scattering Transform of Vibration Data in another window
Topics: Bearings, Condition monitoring, Electromagnetic scattering, Radiation scattering, Scattering (Physics), Vibration, 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

Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions

Alexandre Mauricio, Dustin Helm, Markus Timusk, Jerome Antoni, Konstantinos Gryllias
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A018, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-15245
https://doi.org/10.1115/GT2020-15245
View Paper titled, Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions
Open the PDF for Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions in another window
Topics: Machinery, Stress, Signals, Condition monitoring, Failure, Maintenance, Bearings, Damage, Density, Excitation
Proceedings Papers

Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings

Junyu Qi, Alexandre Mauricio, Konstantinos Gryllias
Proc. ASME. GT2020, Volume 12: Wind Energy, V012T42A008, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-15278
https://doi.org/10.1115/GT2020-15278
View Paper titled, Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings
Open the PDF for Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings in another window
Topics: Bearings, Condition monitoring, Entropy, Mechanical drives, Wind turbines
Journal Articles

Vibration-Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis

Alexandre Mauricio, Linghao Zhou, David Mba, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2020, 142(3): 031010.
Paper No: GTP-19-1314
https://doi.org/10.1115/1.4044453
Published Online: January 29, 2020
View Article titled, Vibration-Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis
Open the PDF for Vibration-Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis in another window
Topics: Bearings, Condition monitoring, Electromagnetic spectrum, Mechanical drives, Optimization, Signals, Vibration, Filtration, Gears, Flaw detection
Journal Articles

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Alexandre Mauricio, Shuangwen Sheng, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2020, 142(3): 031003.
Paper No: GTP-19-1317
https://doi.org/10.1115/1.4044683
Published Online: January 17, 2020
View Article titled, Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions
Open the PDF for Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions in another window
Topics: Bearings, Condition monitoring, Mechanical drives, Optimization, Sensors, Signals, Stress, Wind turbines, Gears, Damage
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
Proceedings Papers

Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis

Alexandre Mauricio, Linghao Zhou, David Mba, Konstantinos Gryllias
Proc. ASME. GT2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A020, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-91150
https://doi.org/10.1115/GT2019-91150
View Paper titled, Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis
Open the PDF for Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis in another window
Topics: Condition monitoring, Vibration, Mechanical drives, Bearings, Maintenance, Accidents, Decision making, Electromagnetic spectrum, Engines, Fatigue
Proceedings Papers

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Alexandre Mauricio, Shuangwen Sheng, Konstantinos Gryllias
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T48A008, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-91136
https://doi.org/10.1115/GT2019-91136
View Paper titled, Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions
Open the PDF for Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions in another window
Topics: Condition monitoring, Wind turbines, Bearings, Machinery, Mechanical drives, Stress, Vibration, Electromagnetic spectrum, Filtration, Internet of things
Journal Articles

Vibration-Based Condition Monitoring of Wind Turbine Gearboxes Based on Cyclostationary Analysis

Alexandre Mauricio, Junyu Qi, Konstantinos Gryllias
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2019, 141(3): 031026.
Paper No: GTP-18-1329
https://doi.org/10.1115/1.4041114
Published Online: November 1, 2018
View Article titled, Vibration-Based Condition Monitoring of Wind Turbine Gearboxes Based on Cyclostationary Analysis
Open the PDF for Vibration-Based Condition Monitoring of Wind Turbine Gearboxes Based on Cyclostationary Analysis in another window
Topics: Bearings, Condition monitoring, Gears, Mechanical drives, Sensors, Signals, Vibration, Wind turbines, Damage, Emission spectroscopy