Fault Diagnostics of Planet Gears in Wind Turbine Using Autocorrelation- based Time Synchronous Averaging (ATSA)



Jong Moon Ha Jungho Park Byeng D. Youn Yoong Ho Jung


A planetary gearbox is widely used in various rotating systems because it can be used as a speed reducer or increaser without change in direction of shaft while transferring great driving power. Despite many attempts it is still challenging to diagnose potential faults of the planetary gearbox because of multiple contacts and axis rotation of planet gears resulting in complex vibration characteristics. This paper thus presents an original method to isolate vibration signals induced by the planet gears from the complex vibration signals for fault diagnostics of the planetary gearbox. First, an in-depth study on the vibration characteristics of planet gears is presented using the autocorrelation function of the vibration signal. The autocorrelation-based time synchronous averaging (ATSA) method is then developed for the isolation of the vibration signals produced by the planet gears. The vibration signals were utilized for extracting health related data which facilitate the efficient fault diagnostics of the planet gears. Case study with a wind turbine testbed showed that the proposed method can diagnose the root crack of the planet gears.

How to Cite

Ha, J. M., Park, J., Youn, B. D., & Jung, Y. H. (2014). Fault Diagnostics of Planet Gears in Wind Turbine Using Autocorrelation- based Time Synchronous Averaging (ATSA). PHM Society European Conference, 2(1). https://doi.org/10.36001/phme.2014.v2i1.1532
Abstract 20 | PDF Downloads 17



Wind Turbine, fault diagnostics, Planetary gearbox, Time Synchronous Averaging (TSA)

Barszcz, T. & Randall, R.B., (2009). Application of spectral kurtosis for detection of a tooth crack in the planetary gear of a wind turbine. Mechanical Systems and Signal Processing, 23(4), pp.1352–1365.
Bendat, J.S. & Piersol, A.G., (2010). Random Data: Analysis and Measurement Procedures, 4th edition, Hoboken, NJ: John Wiley & Sons, Inc
Blough, J.R., (2006). Adaptive Resampling - Transforming From the Time to the Angle Domain. 2006 IMAC-XXIV: Conference & Exposition on Structural Dynamics.
Decker, H.J. & Zakrajsek, J.J., (1999). Comparison of Interpolation Methods as Applied to Time Synchronous Averaging, Cleveland, Ohio: NASA/TM—1999-209086, NASA Glenn Research Center.
Forrester, B.D., (2001). Method for the separation of epicyclic planet gear vibration signatures. US Patent, US 6,298,725 B1.
Hochmam, D. & Sadok, M., (2004). Theory of Synchronous Averaging. IEEE Aerospace Conference Proceedings. IEEE, pp. 3636–3653.
Hood, A. & Darryll, P., (2011). Sun Gear Fault Detection on an OH-58C Helicopter Transmission. American Helicopter Society 67th Annual Forum. American Helicopter Society, pp. 1664–1690.
Jung, Y.H. et al., (2012). Mechanical Fault Imbedding Process for Major Mechanical Parts of Offshore Wind Turbine. Proceedings of the Korean Society of Mechanical Engineers 2012 Spring Annual Meeting. pp. 159–160.
Lewicki, D.G., Ehinger, R.T. & Fetty, J., (2011). Planetary Gearbox Fault Detection Using Vibration Separation Techniques, Cleveland, Ohio: NASA/TM—2011-217127, NASA Glenn Research Center.
Martin, H.R., (1989). Statistical Moment Analysis as a Means of Surface Damage Detection. Proceedings of the 7th International Modal Analysis Conference. McFadden, P.D., (1994). Window Functions for the Calculation of the Time Domain Averages of the Vibration of the Individual Planet Gears and Sun Gear in an Epicyclic Gearbox. Journal of Vibration and Acoustics, 116(2), pp.179–187.
McFadden, P.D. & Howard, I.M., (1990). The detection of Seeded Faults in an Epicyclic Gearbox by Signal Averaging of the Vibration, Austrailia: AR-006-087 / ARL-PROP-R-183, Commonwealth of Australia.
Samuel, P.D., Conroy, J.K. & Pines, D.J., (2004). Planetary Transmission Diagnostics, Cleveland, Ohio: NASA/CR-2004-213068, NASA Glenn Research Center.
Samuel, P.D. & Pines, D.J., (2005). A review of vibrationbased techniques for helicopter transmission diagnostics. Journal of Sound and Vibration, 282(1-2), pp.475–508.
Yu, J., (2011). Early Fault Detection for Gear Shaft and Planetary Gear Based on Wavelet and Hidden Markov Modeling. Degree of Doctor of Philosophy, University of Toronto.
Zakarjsek, J.J., Townsend, D.P. & Decker, H.J., (1993). An Analysis of Gear Fault Detection Methods as Applied to Pitting, Cleveland, Ohio: NASA TM-105950 / AVSCOM 92-C-035, NASA Lewis Research Center.
Technical Papers