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Flaw detection
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Proceedings Papers
Fault Detection on Short-Haul or Highly Dynamic Flights Using Transient Flight Segments
Available to Purchase
Proc. ASME. GT2024, Volume 4: Controls, Diagnostics, and Instrumentation, V004T05A014, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-124026
Proceedings Papers
A Comparative Analysis of Various Machine Learning Approaches for Fault Diagnostics of Hydrogen Fueled Gas Turbines
Available to Purchase
Proc. ASME. GT2024, Volume 4: Controls, Diagnostics, and Instrumentation, V004T05A050, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-129279
Proceedings Papers
Wind Turbine Drivetrain Fault Detection Using Multi-Variate Deep Learning Combined With Signal Processing
Available to Purchase
Proc. ASME. GT2023, Volume 14: Wind Energy, V014T37A003, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101689
Proceedings Papers
Early Fault Detection Using Deep Learning on Compressed Cyclic Spectral Coherence Maps
Available to Purchase
Proc. ASME. GT2023, Volume 14: Wind Energy, V014T37A001, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101596
Proceedings Papers
Application of Machine Learning to Forced Response Predictions of an Industrial Axial Compressor Rotor Blade
Available to Purchase
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
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-82427
Proceedings Papers
Bearing Fault Detection on Wind Turbine Gearbox Vibrations Using Generalized Likelihood Ratio-Based Indicators
Available to Purchase
Proc. ASME. GT2022, Volume 11: Wind Energy, V011T38A005, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-81294
Proceedings Papers
Rapid Defect Detection and Classification in Images Using Convolutional Neural Networks
Available to Purchase
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T05A013, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-59801
Proceedings Papers
A Novel Vibration-Based Fault Detection Approach of Bolted Engineering Structures Without Reference
Available to Purchase
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
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58493
Proceedings Papers
Research on Fault Diagnosis of Steam Turbine Rotor Unbalance and Parallel Misalignment Based on Numerical Simulation and Convolutional Neural Network
Available to Purchase
Proc. ASME. GT2021, Volume 8: Oil and Gas Applications; Steam Turbine, V008T22A019, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-60247
Proceedings Papers
Possibilities and Limitations of Early Fault Detection in Gas Turbines
Available to Purchase
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A034, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-16251
Proceedings Papers
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A022, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-15641
Proceedings Papers
Data Driven Fault Detection of Premixer Centerbody Degradation in a Swirl Combustor
Available to PurchaseRaghul 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
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-14222
Proceedings Papers
Application of Artificial Neural Network Based Gas Path Diagnostics on Gas Pipeline Compressors
Available to Purchase
Proc. ASME. GT2020, Volume 9: Oil and Gas Applications; Organic Rankine Cycle Power Systems; Steam Turbine, V009T21A007, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-15062
Proceedings Papers
Comparative Analysis of Two Gas Turbine Diagnosis Approaches
Available to Purchase
Proc. ASME. GT2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A025, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-91644
Proceedings Papers
Extending Engine Gas Path Analysis Using Full Flight Data
Available to Purchase
Proc. ASME. GT2019, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A004, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90161
Proceedings Papers
Vibration Based Condition Monitoring of Helicopter Gearboxes Based on Cyclostationary Analysis
Available to Purchase
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
Proceedings Papers
A General Diagnostic Methodology for Sensor Fault Detection, Classification and Overall Health State Assessment
Available to Purchase
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A004, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90055
Proceedings Papers
Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions
Available to Purchase
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
Proceedings Papers
Validation of an Advanced Diagnostic Methodology for the Identification and Classification of Gas Turbine Sensor Faults by Means of Field Data
Available to Purchase
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A005, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90056
Proceedings Papers
Vibration Based Condition Monitoring of Wind Turbine Gearboxes Based on Cyclostationary Analysis
Available to Purchase
Proc. ASME. GT2018, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T48A017, June 11–15, 2018
Publisher: American Society of Mechanical Engineers
Paper No: GT2018-76993
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