Speed Estimation in Geared Wind Turbines Using the Maximum Correlation Coefficient



Georgios Alexandros Skrimpas Kun S. Marhadi Bogi Bech Jensen Christian Walsted Sweeney Nenad Mijatovic Joachim Holboell


Valid speed signal is essential for proper condition monitoring of modern variable speed wind turbines. Traditionally, a tachometer mounted on the high speed shaft provides reference for tracking speed dependant frequency components, such as generator speed harmonics and gearbox tooth mesh frequencies. The health assessment of drive train components is limited to broadband measurements when the speed signal is invalid. This condition results in reduced fault detection capabilities and consequently decreased lead time. In this work, a new speed estimation algorithm is presented in order to overcome the above mentioned issues. The high speed stage shaft angular velocity is calculated based on the maximum correlation coefficient between the 1st gear mesh frequency of the last gearbox stage and a pure sinus tone of known frequency and phase. The proposed algorithm utilizes vibration signals from two accelerometers for cross-referencing purposes. The method is tested in three drive train configurations, where 720 sets of vibration signals of 10.24s length, sampled at 25.6kHz are analysed. Consistent speed estimation reaches approximately 98% when two vibration sources are utilized, whereas it is lower when only one source is taken into account. No apparent patterns arise between speed variation levels or power production and the number of invalid outputs, showing the independence of the method from operational parameters.

How to Cite

Alexandros Skrimpas, . G. ., S. Marhadi, K. ., Bech Jensen, B. ., Walsted Sweeney, C. ., Mijatovic, N. ., & Holboell, J. (2015). Speed Estimation in Geared Wind Turbines Using the Maximum Correlation Coefficient. Annual Conference of the PHM Society, 7(1). https://doi.org/10.36001/phmconf.2015.v7i1.2559
Abstract 18 | PDF Downloads 9




Andersson, C., Gutt, S., & Hastings, M. (2007). Cost-effective monitoring solution using external surveillance centre. In The 2nd world congress on engineering asset management (eam) and the 4th international conference on condition monitoring.

Bartelmus, W., & Zimroz, R. (2009). Vibration condition monitoring of planetary gearbox under varying external load. Mechanical Systems and Signal Processing, 23, 246–257.

Bellini, A., Franceschini, G., & Tassoni, C. (2006). Monitoring of induction machines by maximum covariance method for frequency tracking. Industry Applications , IEEE Transactions on, 42(1), 69–78.

Bonnardot, F., Badaloui, M. E., Randall, R. B., Danie’re, J., & Guillet, F. (2005). Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation). Mechanical Systems and Signal Processing, 19, 766 – 785.

Borghesani, P., Pennacchi, P., Randall, R., & Ricci, R. (2012). Order tracking for discrete-random separation in variable speed conditions. Mechanical Systems and Signal Processing, 30, 1 – 22.

Coats, M. D., Sawalhi, N., & Randall, R. (2009). Extraction of tach information from a vibration signal for improved synchronous averaging. In Proceedings of acoustics.

Combet, F., & Zimroz;, R. (2009). A new method for the estimation of the instantaneous speed relative fluctuation in a vibration signal based on the short time scale transform. Mechanical Systems and Signal Processing, 23, 1382 – 1397.

Marhadi, K., & Hilmisson, R. (2013, June). Simple and effective technique for early detection of rolling element bearing fault: A case study in wind turbine application. In International congress of condition monitoring and diagnostic engineering management (pp. 94–97).

Peng, Z., Meng, G., Chu, F., Lang, Z., Zhang, W., & Yang, Y. (2011). Polynomial chirplet transform with application to instantaneous frequency estimation. Instrumentation and Measurement, IEEE Transactions on, 60(9), 3222 – 3229.

Taylor, J. I. (2000). The gear analysis handbook (VIBRATIONS-WILLOWBROOK, Ed.). The Vibration Institute.

Urbanek, J., Zimroz, R., Barszcz, T., & Antoni, J. (n.d.). Reconstruction of rotational speed from vibration signal – comparison of methods. In The ninth conference on condition monitoring and machine failure prevention technologies.

Villa, L. F., Ren ̃ones, A., Pera ́n, 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(6), 2157 – 2168.

Wu, W., Lin, J., Han, S., & Ding, X. (2009). Time domain averaging based on fractional delay filter. Mechanical Systems and Signal Processing, 23, 1447–1457.

Yiakopoulos, C., Gryllias, K., & Antoniadis, I. (2009). Instantaneous frequency in rotating machinery using harmonic signal decomposition (hard) parametric method. In
Proceedings of the asme international design engineering conference and computers and information in engineering conference (pp. 1205 – 1213).

Zhao, M., Lin, J., Wang, X., Lei, Y., & Cao, J. (2013). A tacho-less order tracking technique for large speed variations. Mechanical Systems and Signal Processing, 40, 76 – 90.

Zimroz, R., Millioz, F., Martin, N., et al. (2010). A procedure of vibration analysis from planetary gearbox un- der non-stationary cyclic operations by instantaneous frequency estimation in time-frequency domain. In Seventh international conference on condition monitoring and machinery failure prevention technologies. cm 2010 and mfpt 2010.

Zimroz, R., Urbanek, J., Barszcz, T., Bartelmus, W., Millioz, F., & Martin, N. (2011). Measurement of instantaneous shaft speed by advanced vibration signal processing- application to wind turbine gearbox. Metrology and Measurement Systems, 18(4), 701 – 712.
Technical Papers