One of the most wide spread gearbox topologies in the wind energy sector consists of a slow rotating planetary stage, an intermediate speed parallel stage and finally a high speed parallel stage driving the generator rotor. The shafts of the two latter stages are supported by ball or roller bearings where their outer races are fixed to the gearbox and their inner races rotate at the corresponding shaft speed. Bearing inner race defects are frequently encountered in gearboxes leading to either replacement of the whole unit or exchange of the shaft or bearing where feasible. The present work deals with the evaluation of the development of an inner race defect from surface pitting to race axial crack resulting in excessive rotational looseness, also referred to as bearing creep. It is shown that an inner race defect can be identified efficiently at an early stage by employing well known vibration condition indicators, e.g. crest factor, whereas development to rotational looseness is expressed as increased sideband activity between the gear mesh frequencies spaced at the shaft speed supported by the defective bearing due to abnormal meshing. The condition of the gears and the shaft during the final stage of the above described failure mode is essential in regards to the possibility of uptower repairs or their use in refurbished gearboxes. Case studies from operating multi-megawatt wind turbines are presented, illustrating the progression of the fault via continuous trending of condition indicators and detailed spectral analysis of high resolution vibration signals.
How to Cite
El Morsy, M., & Achtenová, G. (2015). Gear fault diagnosis based on optimal morlet wavelet filter and autocorrelation enhancement. SAE Technical Paper, 1–8.
Feng, Y., Qiu, Y., Crabtree, C. J., Long, H., & Tavner, P. J. (2013). Monitoring wind turbine gearboxes. Wind Energy, 16, 728–740.
Hong, L., Dhupia, J. S., & Sheng, S. (2014). An explanation of frequency features enabling detection of faults in equally spaced planetary gearbox. Meachanism and Machine Theory, 73, 169–183.
Oyague, F. (2009). Gearbox modeling and load simulation of a baseline 750-kw wind turbine using state-of-theart simulation codes (Tech. Rep.). National Renewable Energy Laboratory Golden, CO.
Qu, Y., He, D., Yoon, J., Van Hecke, B., Bechhoefer, E., & Zhu, J. (2014). Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensorsa comparative study. Sensors, 14, 1372–1393.
Siegel, D., Zhao, W., Lapira, E., AbuAli, M., & Lee, J. (2014). A comparative study on vibration-based condition monitoring algorithms for wind turbine drive trains. Wind Energy, 17, 695–714.
Skrimpas, G. A., Marhadi, K., Jensen, B. B., Sweeney, C.W., Mijatovic, N., & Holboell, J. (2015). Speed estimation in geared wind turbines using the maximum correlation coefficient. In Proceedings of the annual conference of the prognostics and health management society 2015.
Skrimpas, G. A., Marhadi, K. S., Gomez, R., Jensen, B. B., Mijatovic, N., & Holbøll, J. (2015). Detection of pitch failures in wind turbines using environmental noise recognition techniques. In Proceedings of the annual conference of the prognostics and health management society 2015.
Villa, L. F., Reñones, A., Perán, J. R., & De Miguel, L. J. (2011). Angular resampling for vibration analysis in wind turbines under non-linear speed fluctuation. Mechanical Systems and Signal Processing, 25, 2157–2168.
Zhang, Z., Verma, A., & Kusiak, A. (2012). Fault analysis and condition monitoring of the wind turbine gearbox. Energy Conversion, IEEE Transactions on, 27, 526–535.
Zhu, J., Nostrand, T., Spiegel, C., & Morton, B. (2014). Survey of condition indicators for condition monitoring systems. In Proceedings of the annual conference of the prognostics and health management society 2014.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.