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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

Paper No: IOWTC2022-98704

DOI: https://doi.org/10.1115/IOWTC2022-98704

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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

Paper No: GT2022-83600

DOI: https://doi.org/10.1115/GT2022-83600

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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

Paper No: GT2022-82624

DOI: https://doi.org/10.1115/GT2022-82624

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Topics: Condition monitoring, Wind turbines

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

J. Eng. Gas Turbines Power. April 2022, 144(4): 041018.

Paper No: GTP-20-1600

DOI: https://doi.org/10.1115/1.4049778

Published Online: February 21, 2022

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Topics: Machinery, Signals, Stress, Damage, Bearings

Journal Articles

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

Junyu Qi, Alexandre Mauricio, Konstantinos Gryllias

J. Eng. Gas Turbines Power. April 2022, 144(4): 041019.

Paper No: GTP-20-1604

DOI: https://doi.org/10.1115/1.4049797

Published Online: February 21, 2022

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Topics: Entropy, Wind turbines, 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

Paper No: GT2021-60280

DOI: https://doi.org/10.1115/GT2021-60280

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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

Paper No: IOWTC2021-3527

DOI: https://doi.org/10.1115/IOWTC2021-3527

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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

Paper No: GT2020-15245

DOI: https://doi.org/10.1115/GT2020-15245

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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

Paper No: GT2020-15278

DOI: https://doi.org/10.1115/GT2020-15278

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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

J. Eng. Gas Turbines Power. March 2020, 142(3): 031010.

Paper No: GTP-19-1314

DOI: https://doi.org/10.1115/1.4044453

Published Online: January 29, 2020

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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

J. Eng. Gas Turbines Power. March 2020, 142(3): 031003.

Paper No: GTP-19-1317

DOI: https://doi.org/10.1115/1.4044683

Published Online: January 17, 2020

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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

Paper No: IOWTC2019-7603

DOI: https://doi.org/10.1115/IOWTC2019-7603

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Topics: Bearings, Condition monitoring, Wind turbines, Ocean engineering, Vibration, Wind, Floating wind turbines, Maintenance, Offshore wind turbines, Wind energy

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

Paper No: GT2019-91136

DOI: https://doi.org/10.1115/GT2019-91136

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Topics: Condition monitoring, Wind turbines, Bearings, Machinery, Mechanical drives, Stress, Vibration, Electromagnetic spectrum, Filtration, Internet of things

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

Paper No: GT2019-91150

DOI: https://doi.org/10.1115/GT2019-91150

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Topics: Condition monitoring, Vibration, Mechanical drives, Bearings, Maintenance, Accidents, Decision making, Electromagnetic spectrum, Engines, Fatigue

Journal Articles

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

Alexandre Mauricio, Junyu Qi, Konstantinos Gryllias

J. Eng. Gas Turbines Power. March 2019, 141(3): 031026.

Paper No: GTP-18-1329

DOI: https://doi.org/10.1115/1.4041114

Published Online: November 1, 2018

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Topics: Bearings, Condition monitoring, Gears, Mechanical drives, Sensors, Signals, Vibration, Wind turbines, Damage, Emission spectroscopy

Proceedings Papers

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

Alexandre Mauricio, Junyu Qi, Konstantinos Gryllias

Proc. ASME. GT2018, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T48A017, June 11–15, 2018

Paper No: GT2018-76993

DOI: https://doi.org/10.1115/GT2018-76993

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Topics: Condition monitoring, Vibration, Wind turbines, Bearings, Filtration, Mechanical drives, Electromagnetic spectrum, Machinery, Rolling bearings, Signals

Journal Articles

Application of Cyclo-Nonstationary Indicators for Bearing Monitoring Under Varying Operating Conditions

Konstantinos Gryllias, Simona Moschini, Jerome Antoni

J. Eng. Gas Turbines Power. January 2018, 140(1): 012501.

Paper No: GTP-17-1243

DOI: https://doi.org/10.1115/1.4037638

Published Online: September 19, 2017

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Topics: Aircraft engines, Bearings, Mechanical drives, Signals, Vibration, Engines, Rolling bearings

Proceedings Papers

Application of Cyclo-Non-Stationary Indicators for Bearing Monitoring Under Varying Operating Conditions

Konstantinos Gryllias, Simona Moschini, Jerome Antoni

Proc. ASME. GT2017, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A021, June 26–30, 2017

Paper No: GT2017-64443

DOI: https://doi.org/10.1115/GT2017-64443

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Topics: Bearings, Machinery, Signals, Condition monitoring, Engines, Aircraft engines, Maintenance, Stress, Vibration, Acoustics

Proceedings Papers

Virtual Sensing for Rotordynamics

Simona Moschini, Konstantinos Gryllias, Wim Desmet, Bert Pluymers

Proc. ASME. GT2016, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A017, June 13–17, 2016

Paper No: GT2016-57206

DOI: https://doi.org/10.1115/GT2016-57206

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Topics: Rotordynamics, Algorithms, Computer simulation, Disperse systems, Energy efficiency, Fossil fuels, Kalman filters, Machinery, Monitoring systems, Rotors

Proceedings Papers

Rolling Element Bearing Fault Classification Using K-Means Frequency Domain Based Clustering

Christos Yiakopoulos, Konstantinos Gryllias, Ioannis Antoniadis

Proc. ASME. IDETC-CIE2009, Volume 1: 22nd Biennial Conference on Mechanical Vibration and Noise, Parts A and B, 127-134, August 30–September 2, 2009

Paper No: DETC2009-87369

DOI: https://doi.org/10.1115/DETC2009-87369

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Topics: Algorithms, Artificial neural networks, Bearings, Computer programming, Condition monitoring, Fault diagnosis, Machinery, Reliability, Rolling bearings, Signals

Journal citation

NARROW

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

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

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

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

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

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

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

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

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

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

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Condition Monitoring of Wind Turbine Drivetrain Bearings

Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis

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

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

Application of Cyclo-Nonstationary Indicators for Bearing Monitoring Under Varying Operating Conditions

Application of Cyclo-Non-Stationary Indicators for Bearing Monitoring Under Varying Operating Conditions

Virtual Sensing for Rotordynamics

Rolling Element Bearing Fault Classification Using K-Means Frequency Domain Based Clustering

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