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Proceedings Papers

Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade

Giuseppe Bruni, Senthil Krishnababu, Simon Jackson
Proc. ASME. GT2022, Volume 8A: Structures and Dynamics — Aerodynamics Excitation and Damping; Bearing and Seal Dynamics; Emerging Methods in Engineering Design, Analysis, and Additive Manufacturing; Fatigue, Fracture, and Life Prediction, V08AT21A019, June 13–17, 2022
Paper No: GT2022-82427
DOI: https://doi.org/10.1115/GT2022-82427
View Paper titled, Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade
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Topics: Blades, Compressors, Machine learning, Rotors, Design, Artificial neural networks, Computational fluid dynamics, Algorithms, Cycles, Damping
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
DOI: https://doi.org/10.1115/GT2022-81294
View Paper titled, Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators
Click here to open pdf in another window PDF for Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators
Topics: Bearings, Condition monitoring, Flaw detection, Mechanical drives, Vibration, Wind turbines
Proceedings Papers

Research on Fault Diagnosis of Steam Turbine Rotor Unbalance and Parallel Misalignment Based on Numerical Simulation and Convolutional Neural Network

Chongyu Wang, Di Zhang, Yonghui Xie
Proc. ASME. GT2021, Volume 8: Oil and Gas Applications; Steam Turbine, V008T22A019, June 7–11, 2021
Paper No: GT2021-60247
DOI: https://doi.org/10.1115/GT2021-60247
View Paper titled, Research on Fault Diagnosis of Steam Turbine Rotor Unbalance and Parallel Misalignment Based on Numerical Simulation and Convolutional Neural Network
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Topics: Artificial neural networks, Computer simulation, Fault diagnosis, Flaw detection, Rotors, Steam turbines
Proceedings Papers

A Novel Vibration-Based Fault Detection Approach of Bolted Engineering Structures Without Reference

Quankun Li, Zengde Shao, Mingfu Liao
Proc. ASME. GT2021, Volume 9B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V09BT26A002, June 7–11, 2021
Paper No: GT2021-58493
DOI: https://doi.org/10.1115/GT2021-58493
View Paper titled, A Novel Vibration-Based Fault Detection Approach of Bolted Engineering Structures Without Reference
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Topics: Bolted joints, Flaw detection, Structures, Vibration
Proceedings Papers

Rapid Defect Detection and Classification in Images Using Convolutional Neural Networks

Peter Warren, Hessein Ali, Hossein Ebrahimi, Ranajay Ghosh
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T05A013, June 7–11, 2021
Paper No: GT2021-59801
DOI: https://doi.org/10.1115/GT2021-59801
View Paper titled, Rapid Defect Detection and Classification in Images Using Convolutional Neural Networks
Click here to open pdf in another window PDF for Rapid Defect Detection and Classification in Images Using Convolutional Neural Networks
Topics: Artificial neural networks, Flaw detection, Optical quality control, Machine learning, Image processing, Inspection, Manufacturing, Nondestructive evaluation, Turbomachinery
Proceedings Papers

Application of Artificial Neural Network Based Gas Path Diagnostics on Gas Pipeline Compressors

Suleiman M. Suleiman, Yi-Guang Li
Proc. ASME. GT2020, Volume 9: Oil and Gas Applications; Organic Rankine Cycle Power Systems; Steam Turbine, V009T21A007, September 21–25, 2020
Paper No: GT2020-15062
DOI: https://doi.org/10.1115/GT2020-15062
View Paper titled, Application of Artificial Neural Network Based Gas Path Diagnostics on Gas Pipeline Compressors
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Topics: Artificial neural networks, Compressors, Pipelines, Compression, Corrosion, Erosion, Errors, Flaw detection, Flow (Dynamics), Instrumentation
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
DOI: 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

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
DOI: 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

A Comprehensive Modeling of Centrifugal Compressor Vibrations for Early Fault Detection

François Libeyre, Francis Bainier, Pascal Alas
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A022, September 21–25, 2020
Paper No: GT2020-15641
DOI: https://doi.org/10.1115/GT2020-15641
View Paper titled, A Comprehensive Modeling of Centrifugal Compressor Vibrations for Early Fault Detection
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Topics: Compressors, Flaw detection, Modeling, Vibration
Proceedings Papers

A General Diagnostic Methodology for Sensor Fault Detection, Classification and Overall Health State Assessment

Lucrezia Manservigi, Mauro Venturini, Giuseppe Fabio Ceschini, Giovanni Bechini, Enzo Losi
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A004, June 17–21, 2019
Paper No: GT2019-90055
DOI: https://doi.org/10.1115/GT2019-90055
View Paper titled, A General Diagnostic Methodology for Sensor Fault Detection, Classification and Overall Health State Assessment
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Topics: Flaw detection, Sensors, Gas turbines, Machinery, Signals
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
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

Validation of an Advanced Diagnostic Methodology for the Identification and Classification of Gas Turbine Sensor Faults by Means of Field Data

Lucrezia Manservigi, Mauro Venturini, Giuseppe Fabio Ceschini, Giovanni Bechini, Enzo Losi
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A005, June 17–21, 2019
Paper No: GT2019-90056
DOI: https://doi.org/10.1115/GT2019-90056
View Paper titled, Validation of an Advanced Diagnostic Methodology for the Identification and Classification of Gas Turbine Sensor Faults by Means of Field Data
Click here to open pdf in another window PDF for Validation of an Advanced Diagnostic Methodology for the Identification and Classification of Gas Turbine Sensor Faults by Means of Field Data
Topics: Gas turbines, Sensors, Sensitivity analysis, Flaw detection, Signals
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
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

Comparative Analysis of Two Gas Turbine Diagnosis Approaches

Igor Loboda, Juan Luis Pérez-Ruiz, Sergiy Yepifanov, Roman Zelenskyi
Proc. ASME. GT2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A025, June 17–21, 2019
Paper No: GT2019-91644
DOI: https://doi.org/10.1115/GT2019-91644
View Paper titled, Comparative Analysis of Two Gas Turbine Diagnosis Approaches
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Topics: Gas turbines, Physics, Engines, Pattern recognition, Flaw detection, Algorithms, Artificial neural networks, Damage, Errors, Parameter estimation
Proceedings Papers

Extending Engine Gas Path Analysis Using Full Flight Data

Liang Tang, Allan J. Volponi, Ethan Prihar
Proc. ASME. GT2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A004, June 17–21, 2019
Paper No: GT2019-90161
DOI: https://doi.org/10.1115/GT2019-90161
View Paper titled, Extending Engine Gas Path Analysis Using Full Flight Data
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Topics: Engines, Flight, Compressors, Flaw detection, Steady state, Algorithms, Delays, Fuel consumption, Maintenance, Sensors
Proceedings Papers

A Benchmarking Analysis of a Data-Driven Gas Turbine Diagnostic Approach

Igor Loboda, Juan Luis Pérez-Ruiz, Sergiy Yepifanov
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A027, June 11–15, 2018
Paper No: GT2018-76887
DOI: https://doi.org/10.1115/GT2018-76887
View Paper titled, A Benchmarking Analysis of a Data-Driven Gas Turbine Diagnostic Approach
Click here to open pdf in another window PDF for A Benchmarking Analysis of a Data-Driven Gas Turbine Diagnostic Approach
Topics: Gas turbines, Algorithms, Flaw detection, Engines, Feature extraction, Aircraft engines, Computer software, Monitoring systems, Pattern recognition, Polynomials
Proceedings Papers

Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines

Valentina Zaccaria, Mikael Stenfelt, Ioanna Aslanidou, Konstantinos G. Kyprianidis
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A021, June 11–15, 2018
Paper No: GT2018-76414
DOI: https://doi.org/10.1115/GT2018-76414
View Paper titled, Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines
Click here to open pdf in another window PDF for Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines
Topics: Aircraft, Aircraft engines, Engines, Failure, Flaw detection, Flight, Fuel consumption, Machine learning, Maintenance, Physics
Proceedings Papers

A Two-Layer Multi-Model Gas Path Fault Diagnosis Method

Yunpeng Cao, Yinghui He, Fang Yu, Jianwei Du, Shuying Li, Qingcai Yang, Rui Liu
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A009, June 11–15, 2018
Paper No: GT2018-75368
DOI: https://doi.org/10.1115/GT2018-75368
View Paper titled, A Two-Layer Multi-Model Gas Path Fault Diagnosis Method
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Topics: Fault diagnosis, Flaw detection, Gas turbines, Algorithms, Simulation, Artificial neural networks, Probability, Statistics
Proceedings Papers

Automated Condition Evaluation of Hot-Gas Path Components of Jet Engines Through Exhaust Jet Analysis

Ulrich Hartmann, Joerg R. Seume
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A011, June 11–15, 2018
Paper No: GT2018-75384
DOI: https://doi.org/10.1115/GT2018-75384
View Paper titled, Automated Condition Evaluation of Hot-Gas Path Components of Jet Engines Through Exhaust Jet Analysis
Click here to open pdf in another window PDF for Automated Condition Evaluation of Hot-Gas Path Components of Jet Engines Through Exhaust Jet Analysis
Topics: Exhaust systems, Jet engines, Density, Algorithms, Support vector machines, Aircraft engines, Blades, Computational fluid dynamics, Engineering simulation, Film cooling
Proceedings Papers

Automated Gas Turbine Sensor Fault Diagnostics

Gbanaibolou Jombo, Yu Zhang, Jonathan David Griffiths, Tony Latimer
Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A003, June 11–15, 2018
Paper No: GT2018-75229
DOI: https://doi.org/10.1115/GT2018-75229
View Paper titled, Automated Gas Turbine Sensor Fault Diagnostics
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Topics: Gas turbines, Sensors, Signals, Discrete wavelet transforms, Failure, Flaw detection, Testing, Transients (Dynamics), Wavelets