Fault detection in complex mechanical systems such as wind turbine gearboxes remains challenging, even with the recently significant advancement of sensing and signal processing technologies. As first-principle models of gearboxes capable of reflecting response details for health monitoring purpose are difficult to obtain, data-driven approaches are often adopted for fault detection, identification or classification. In this paper, we propose a data-driven framework that combines information from multiple sensors and fundamental physics of the gearbox. Time domain vibration and acoustic emission signals are collected from a gearbox dynamics testbed, where both healthy and faulty gears with different fault conditions are tested. To deal with the nonstationary nature of the wind turbine operation, a harmonic wavelet based method is utilized to extract the time-frequency features in the signals. This new framework features the employment of the tachometer readings and gear meshing relationships to develop a speed profile masking technique. The time-frequency wavelet features are highlighted by applying the mask we construct. Those highlighted features from multiple accelerometers and microphones are then fused together through a statistical weighting approach based on principal component analysis. Using the highlighted and fused features, we demonstrate that different gear faults can be effectively detected and identified.
Skip Nav Destination
e-mail: jtang@engr.uconn.edu
Article navigation
April 2012
Research Papers
Wind Turbine Gearbox Fault Detection Using Multiple Sensors With Features Level Data Fusion
Y. Lu,
Y. Lu
Graduate Research Assistant
Department of Mechanical Engineering,
University of Connecticut
, 191 Auditorium Road, Unit 3139, Storrs, CT 06269
Search for other works by this author on:
J. Tang,
J. Tang
Associate Professor
Department of Mechanical Engineering,
e-mail: jtang@engr.uconn.edu
University of Connecticut
, 191 Auditorium Road, Unit 3139, Storrs, CT 06269
Search for other works by this author on:
H. Luo
H. Luo
Global Technical Leader – Wind, Machinery Diagnostics Services, GE Energy Services
, 1 River Road, Schenectady, NY 12345
Search for other works by this author on:
Y. Lu
Graduate Research Assistant
Department of Mechanical Engineering,
University of Connecticut
, 191 Auditorium Road, Unit 3139, Storrs, CT 06269
J. Tang
Associate Professor
Department of Mechanical Engineering,
University of Connecticut
, 191 Auditorium Road, Unit 3139, Storrs, CT 06269e-mail: jtang@engr.uconn.edu
H. Luo
Global Technical Leader – Wind, Machinery Diagnostics Services, GE Energy Services
, 1 River Road, Schenectady, NY 12345J. Eng. Gas Turbines Power. Apr 2012, 134(4): 042501 (8 pages)
Published Online: January 25, 2012
Article history
Received:
May 5, 2011
Revised:
May 9, 2011
Online:
January 25, 2012
Published:
January 25, 2012
Citation
Lu, Y., Tang, J., and Luo, H. (January 25, 2012). "Wind Turbine Gearbox Fault Detection Using Multiple Sensors With Features Level Data Fusion." ASME. J. Eng. Gas Turbines Power. April 2012; 134(4): 042501. https://doi.org/10.1115/1.4004438
Download citation file:
Get Email Alerts
Image-based flashback detection in a hydrogen-fired gas turbine using a convolutional autoencoder
J. Eng. Gas Turbines Power
Fuel Thermal Management and Injector Part Design for LPBF Manufacturing
J. Eng. Gas Turbines Power
An investigation of a multi-injector, premix/micromix burner burning pure methane to pure hydrogen
J. Eng. Gas Turbines Power
Related Articles
Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response due to Foreign Object Damage (FOD) Events
J. Eng. Gas Turbines Power (July,2007)
Vibration-Based Condition Monitoring of Wind Turbine Gearboxes Based on Cyclostationary Analysis
J. Eng. Gas Turbines Power (March,2019)
Detection of Self-Stimulatory Behaviors of Children with Autism Using Wearable and Environmental Sensors
J. Med. Devices (June,2009)
Degradation Assessment and Fault Modes Classification Using Logistic Regression
J. Manuf. Sci. Eng (November,2005)
Related Proceedings Papers
Related Chapters
Introduction I: Role of Engineering Science
Fundamentals of heat Engines: Reciprocating and Gas Turbine Internal Combustion Engines
Design of a Tri-Axial Accelerometer for Low Frequency Vibration
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Trend and XY Plots
Fundamentals of Rotating Machinery Diagnostics