WAVELET-BASED ALGORITHM FOR DETECTION OF BEARING FAULTS IN A GAS TURBINE ENGINE
DOI:
https://doi.org/10.18372/2306-1472.59.6798Keywords:
bearing faults, complex Morlet wavelet, gas turbine engine, wavelet scalogram and ridgesAbstract
Presented is a gas turbine engine bearing diagnostic system that integrates information from various advanced vibration analysis techniques to achieve robust bearing health state awareness. This paper presents a computational algorithm for identifying power frequency variations and integer harmonics by using wavelet-based transform. The continuous wavelet transform with the complex Morlet wavelet is adopted to detect the harmonics presented in a power signal. The algorithm based on the discrete stationary wavelet transform is adopted to denoise the wavelet ridges.
References
Berezhnoy, V.Y.; Degtyarev, O.D.; Kudin, M.M.; Saveliev, O.P. The use of modern methods of analysis for the study of non-stationary signals for vibration GTE on ransients.Aerospace engineering and technology. 2008. N 10 (57). P. 184–187 (in Russian).
Carmona, R. A.; Hwang, W. L.; Torresan, B. Characterization of signals by the ridges of their wavelet transforms. IEEE Transactions on Signal Processing. 2005. Vol. 45, N 10. P. 2586–2590.
Defect detection of rolling bearings (translated materials of company IRD). Available from Internet: <http://www.vibration.ru/obnar_defekt.shtml> (in Russian).
Huang, S.-J.; Hsieh, C.-T.; Huang, C.-L. Application of Morlet wavelets to supervise power system disturbances. IEEE Transactions on Power Delivery. 2009. Vol. 14, N. 1. P. 235–241.
Pham, V. L.;Wong, K. P. Wavelet-transform-based algorithm for harmonic analysis of power system waveforms. IEE Proceedings: Generation, Transmission and Distribution. 2007. Vol. 146, N 3. P. 249–254.
Sinyakov, A. N.; Shamayrdanov, F. A. Automatic control system of aircraft and propulsion systems. Mechanical engineering. 1991. P. 320 (in Russian).
Tereshchenko, J. M.; Kulik, M. S.; Panin, V. V. Theory of aviation gas turbine engine. 2005. P. 500 (in Russian).
Zhernakov S. V. Algorithms for control and diagnostics of aircraft gas turbine engine conditions onboard implementation based on neural network technology. 2010. N 3 (38). P. 42-56 (in Russian).
Carmona, R. A.; Hwang, W. L.; Torresan, B. Characterization of signals by the ridges of their wavelet transforms. IEEE Transactions on Signal Processing. 2005. Vol. 45, N 10. P. 2586–2590.
Defect detection of rolling bearings (translated materials of company IRD). Available from Internet: <http://www.vibration.ru/obnar_defekt.shtml> (in Russian).
Huang, S.-J.; Hsieh, C.-T.; Huang, C.-L. Application of Morlet wavelets to supervise power system disturbances. IEEE Transactions on Power Delivery. 2009. Vol. 14, N. 1. P. 235–241.
Pham, V. L.;Wong, K. P. Wavelet-transform-based algorithm for harmonic analysis of power system waveforms. IEE Proceedings: Generation, Transmission and Distribution. 2007. Vol. 146, N 3. P. 249–254.
Sinyakov, A. N.; Shamayrdanov, F. A. Automatic control system of aircraft and propulsion systems. Mechanical engineering. 1991. P. 320 (in Russian).
Tereshchenko, J. M.; Kulik, M. S.; Panin, V. V. Theory of aviation gas turbine engine. 2005. P. 500 (in Russian).
Zhernakov S. V. Algorithms for control and diagnostics of aircraft gas turbine engine conditions onboard implementation based on neural network technology. 2010. N 3 (38). P. 42-56 (in Russian).
Downloads
Published
04-07-2014
How to Cite
Enchev, S., & Tovkach, S. (2014). WAVELET-BASED ALGORITHM FOR DETECTION OF BEARING FAULTS IN A GAS TURBINE ENGINE. Proceedings of National Aviation University, 59(2), 88–96. https://doi.org/10.18372/2306-1472.59.6798
Issue
Section
MODERN AVIATION AND SPACE TEHNOLOGY
