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Proceedings Papers

Condition Monitoring Insight Using Bayesian Inference and Rotor Dynamics Modelling for Rotating Machinery

Greg Nelson, Iain Palmer
Proc. ASME. GT2022, Volume 8B: Structures and Dynamics — Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V08BT25A002, June 13–17, 2022
Paper No: GT2022-80976
https://doi.org/10.1115/GT2022-80976
View Paper titled, Condition Monitoring Insight Using Bayesian Inference and Rotor Dynamics Modelling for Rotating Machinery
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Topics: Condition monitoring, Machinery, Modeling, Rotordynamics, Vibration, Bearings, Clearances (Engineering), Compressors, Digital twin, Finite element model
Proceedings Papers

Unsupervised Feature Selection of Multi-Sensor SCADA Data in Horizontal Axis Wind Turbine Condition Monitoring

Eric Stefan Miele, Fabrizio Bonacina, Alessandro Corsini, Arianna Peruch, Marco Cannarozzo, Daniele Baldan, Francesco Pennisi
Proc. ASME. GT2022, Volume 11: Wind Energy, V011T38A015, June 13–17, 2022
Paper No: GT2022-82462
https://doi.org/10.1115/GT2022-82462
View Paper titled, Unsupervised Feature Selection of Multi-Sensor SCADA Data in Horizontal Axis Wind Turbine Condition Monitoring
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Topics: Condition monitoring, Feature selection, Horizontal axis wind turbines, Sensors
Proceedings Papers

Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators

Kayacan Kestel, Cédric Peeters, Jérôme Antoni, Shawn Sheng, Jan Helsen
Proc. ASME. GT2022, Volume 11: Wind Energy, V011T38A005, June 13–17, 2022
Paper No: GT2022-81294
https://doi.org/10.1115/GT2022-81294
View Paper titled, Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators
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Topics: Bearings, Condition monitoring, Flaw detection, Mechanical drives, Vibration, 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
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
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Topics: Condition monitoring, Wind turbines
Proceedings Papers

Transient Engine Condition Monitoring of Micro Gas Turbines in a Highly Dynamic Setting

Tihomir Varchev, Matthias Weiss, Stephan Staudacher, Christian Koch
Proc. ASME. GT2022, Volume 2: Coal, Biomass, Hydrogen, and Alternative Fuels; Controls, Diagnostics, and Instrumentation; Steam Turbine, V002T05A013, June 13–17, 2022
Paper No: GT2022-82377
https://doi.org/10.1115/GT2022-82377
View Paper titled, Transient Engine Condition Monitoring of Micro Gas Turbines in a Highly Dynamic Setting
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Topics: Condition monitoring, Engines, Micro gas turbines, Transients (Dynamics), Flight, Artificial neural networks, Flow (Dynamics), Measurement uncertainty, Noise (Sound), Wavelets
Proceedings Papers

The Application of an Artificial Neural Network As a Baseline Model For Condition Monitoring of Innovative Humidified Micro Gas Turbine Cycles

Kathryn Colquhoun, Homam Nikpey Somehsaraei, Ward De Paepe
Proc. ASME. GT2022, Volume 4: Cycle Innovations; Cycle Innovations: Energy Storage, V004T06A021, June 13–17, 2022
Paper No: GT2022-82444
https://doi.org/10.1115/GT2022-82444
View Paper titled, The Application of an Artificial Neural Network As a Baseline Model For Condition Monitoring of Innovative Humidified Micro Gas Turbine Cycles
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Topics: Artificial neural networks, Condition monitoring, Cycles, Micro gas turbines
Proceedings Papers

A Proven Engine Optimizer for the Aeroderivative Industry: Challenges and Solutions

Nicolas Demougeot, Franklin van den Hout, Danny Grobbe, Wenping Wang
Proc. ASME. GT2022, Volume 5: Education; Electric Power; Fans and Blowers, V005T09A009, June 13–17, 2022
Paper No: GT2022-83026
https://doi.org/10.1115/GT2022-83026
View Paper titled, A Proven Engine Optimizer for the Aeroderivative Industry: Challenges and Solutions
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Topics: Engines, Gas turbines, Emissions, Dynamic models, Combustion systems, Combustion, Control equipment, Dynamics (Mechanics), Combustion chambers, Computer software
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
https://doi.org/10.1115/GT2021-60280
View Paper titled, Condition Monitoring of Wind Turbines Based on the Scattering Transform of Vibration Data
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Topics: Bearings, Condition monitoring, Electromagnetic scattering, Radiation scattering, Scattering (Physics), Vibration, Wind turbines
Proceedings Papers

Possibilities and Limitations of Early Fault Detection in Gas Turbines

Bernhard Persigehl, Thomas Gellermann, Stefan Thumm, Johannes Stoiber
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A034, September 21–25, 2020
Paper No: GT2020-16251
https://doi.org/10.1115/GT2020-16251
View Paper titled, Possibilities and Limitations of Early Fault Detection in Gas Turbines
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Topics: Flaw detection, Gas turbines, Maintenance, Failure, Damage, Condition monitoring
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
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
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Topics: Machinery, Stress, Signals, Condition monitoring, Failure, Maintenance, Bearings, Damage, Density, Excitation
Proceedings Papers

Real Time Diagnostic Method of Gas Turbines Operating Under Transient Conditions in Hybrid Power Plants

Elias Tsoutsanis, Moussa Hamadache, Roger Dixon
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A013, September 21–25, 2020
Paper No: GT2020-14748
https://doi.org/10.1115/GT2020-14748
View Paper titled, Real Time Diagnostic Method of Gas Turbines Operating Under Transient Conditions in Hybrid Power Plants
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Topics: Gas turbines, Hybrid power systems, Transients (Dynamics), Engines, Stress, Wind farms, Condition monitoring, Electric power generation, Maintenance, Renewable energy
Proceedings Papers

Dynamic Gas Turbine Condition Monitoring Scheme With Multi-Part Neural Network

Zhouzheng Li, Kun Feng, Binbin Yan
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A007, September 21–25, 2020
Paper No: GT2020-14454
https://doi.org/10.1115/GT2020-14454
View Paper titled, Dynamic Gas Turbine Condition Monitoring Scheme With Multi-Part Neural Network
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Topics: Artificial neural networks, Condition monitoring, Failure, Gas turbines
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
https://doi.org/10.1115/GT2020-15278
View Paper titled, Comparison of Blind Diagnostic Indicators for Condition Monitoring of Wind Turbine Gearbox Bearings
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Topics: Bearings, Condition monitoring, Entropy, Mechanical drives, Wind turbines
Proceedings Papers

On the Effects of a Shaft Crack Propagation on the Dynamic Behavior of a Steam Turbine

Steven Chatterton, Paolo Pennacchi, Andrea Vania
Proc. ASME. GT2020, Volume 10B: Structures and Dynamics, V10BT29A003, September 21–25, 2020
Paper No: GT2020-14207
https://doi.org/10.1115/GT2020-14207
View Paper titled, On the Effects of a Shaft Crack Propagation on the Dynamic Behavior of a Steam Turbine
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Topics: Crack propagation, Fracture (Materials), Machinery, Steam turbines, Vibration, Cross section (Physics), Condition monitoring, Fatigue cracks, Fault diagnosis, Probes
Proceedings Papers

Cyclostationary Approach for Instabilities Detection and Condition Monitoring of Centrifugal Compressor

Mateusz Stajuda, David Garcia Cava, Grzegorz Liśkiewicz
Proc. ASME. GT2020, Volume 2E: Turbomachinery, V02ET41A032, September 21–25, 2020
Paper No: GT2020-15699
https://doi.org/10.1115/GT2020-15699
View Paper titled, Cyclostationary Approach for Instabilities Detection and Condition Monitoring of Centrifugal Compressor
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Topics: Compressors, Condition monitoring
Proceedings Papers

Data Driven Fault Detection of Premixer Centerbody Degradation in a Swirl Combustor

Raghul Manosh Kumar, Benjamin Peters, Benjamin Emerson, Kamran Paynabar, Nagi Gebraeel, Timothy Lieuwen
Proc. ASME. GT2020, Volume 4A: Combustion, Fuels, and Emissions, V04AT04A007, September 21–25, 2020
Paper No: GT2020-14222
https://doi.org/10.1115/GT2020-14222
View Paper titled, Data Driven Fault Detection of Premixer Centerbody Degradation in a Swirl Combustor
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Topics: Combustion chambers, Condition monitoring, Flaw detection, Algorithms, Flames, Gas turbines, Sensors, Sound pressure
Proceedings Papers

Gas Path Diagnostics for a Once-Through Steam Generator

Yu-Zhi Chen, Yi-Guang Li, Mike A. Newby
Proc. ASME. GT2019, Volume 3: Coal, Biomass, Hydrogen, and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration; Organic Rankine Cycle Power Systems, V003T23A004, June 17–21, 2019
Paper No: GT2019-90324
https://doi.org/10.1115/GT2019-90324
View Paper titled, Gas Path Diagnostics for a Once-Through Steam Generator
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Topics: Boilers, Condition monitoring, Heat transfer, Maintenance, Newton's method, Noise (Sound), Power stations, Steam, Water
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
https://doi.org/10.1115/GT2019-91150
View Paper titled, Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis
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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
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
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Topics: Condition monitoring, Wind turbines, Bearings, Machinery, Mechanical drives, Stress, Vibration, Electromagnetic spectrum, Filtration, Internet of things
Proceedings Papers

Linking MRO to Prognosis Based Health Management Through Physics-of-Failures Understanding

Prakash Patnaik, Xijia Wu
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T24A007, June 11–15, 2018
Paper No: GT2018-75395
https://doi.org/10.1115/GT2018-75395
View Paper titled, Linking MRO to Prognosis Based Health Management Through Physics-of-Failures Understanding
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Topics: Failure, Physics, Maintenance, Failure mechanisms, Creep, Engines, Fatigue, Condition monitoring, Databases, High cycle fatigue