This paper investigates a machinery health monitoring method using dynamic gearbox models (DGM) and harmonic wavelet transforms (HWT) for vibration response analysis. Gearbox vibration measurement is typically processed via frequency spectrum analysis to identify faults. However, the gearbox system may operate with varying rotational speed, as in many types of wind turbines. In such applications, harmonic wavelet transform analysis has been shown to capture the physics of events with minimal leakage between frequency bands, good frequency resolution and good time resolution. Implementing HWT signal processing for fault detection requires the development of libraries of healthy and faulty gear states to use with pattern recognition. The development of DGM can help to greatly reduce the library development and provide a physically meaningful connection of fault indicators to the actual fault patterns. In this research, a comprehensive DGM is developed, followed by HWT analyses to illustrate the fault detection and diagnosis procedure and capability.
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ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
October 17–19, 2012
Fort Lauderdale, Florida, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4531-8
PROCEEDINGS PAPER
Gear Fault Modeling and Vibration Response Analysis
Edward J. Diehl,
Edward J. Diehl
University of Connecticut, Storrs, CT
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Hans DeSmidt
Hans DeSmidt
University of Tennessee, Knoxville, TN
Search for other works by this author on:
Edward J. Diehl
University of Connecticut, Storrs, CT
J. Tang
University of Connecticut, Storrs, CT
Hans DeSmidt
University of Tennessee, Knoxville, TN
Paper No:
DSCC2012-MOVIC2012-8842, pp. 709-718; 10 pages
Published Online:
September 17, 2013
Citation
Diehl, EJ, Tang, J, & DeSmidt, H. "Gear Fault Modeling and Vibration Response Analysis." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 3: Renewable Energy Systems; Robotics; Robust Control; Single Track Vehicle Dynamics and Control; Stochastic Models, Control and Algorithms in Robotics; Structure Dynamics and Smart Structures; Surgical Robotics; Tire and Suspension Systems Modeling; Vehicle Dynamics and Control; Vibration and Energy; Vibration Control. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 709-718. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8842
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