Abstract
The automatic detection of the vibration signature of rotating parts of an aircraft engine is considered. This paper introduces an algorithm that takes into account the variation over time of the level of detection of orders, i.e. vibrations ate multiples of the rotating speed. The detection level over time at a specific order are gathered in a so-called trajectory. It is shown that clustering the trajectories to classify them into detected and non-detected orders improves the robustness to noise and other external conditions, compared to a traditional statistical signal detection by an hypothesis test. The algorithms are illustrated in real aircraft engine data.
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References
Bladh, R.: Efficient predictions of the vibratory response of mistuned bladed disks by reduced order modeling. PhD thesis, University of Michigan (July 2001)
Braun, S.: Mechanical Signature Analysis: theory and Applications. Academic Press, New York (1986)
Boashash, B.: Time-frequency signal analysis and processing - A comprehensive reference. Elsevier, Amsterdam (2003)
Randall: State of art in monitoring rotating machinery - Part I. Sound and Vibration 38(3), 14–21 (2004)
Muszynska, A.: Rotordynamics. Taylor & Francis, Abington (2005)
Lyon, R.: Machinery Noise and Diagnostics. Butterworths, Boston (1987)
Peng, Z.K., Chu, F.L.: Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mechanical Systems and Signal Processing 18(2), 199–221 (2004)
Mallat, S.: Une exploration des signaux en ondelettes. Publications Ecole Polytechnique (2000)
Kay, S.: Fundamentals of statistical signal processing: detection theory. Prentice-Hall, Englewood Cliffs (1998)
Poor, H.: An introduction to signal detection and estimation, 2nd edn. Springer, Berlin (1994)
Van Trees, H.: Detection, estimation, and modulation theory-Part 1. John Wiley and Sons, Chichester (2001)
Basseville, M., Nikiforov, I.V.: Detection of abrupt changes: theory and application. Prentice-Hall, Englewood Cliffs (1993)
Gertler, J.: Fault detection and diagnosis in engineering systems. CRC Press, Boca Raton (1998)
Tumer, I., Bajwa, A.: A survey of aircraft engine health monitoring systems. In: 35th Joint Propulsion Conference. AIAA (June 1999)
Jaw, L.C., Mattingly, J.D.: Aircraft Engine Controls: Design, System Analysis, and Health Monitoring. AIAA Education Series (2009)
Peng, Z.K., Chu, F.L., Tse, P.W.: Detection of the rubbing-caused impacts for rotor-stator fault diagnosis using reassigned scalogram. Mechanical Systems and Signal Processing 19(2), 391–409 (2005)
Kharyton, V.: Fault detection of blades in blades ov an aviation engines in operation. PhD thesis, Ecole Centrale de Lyon (2009)
Orsagh, R., Sheldon, J., Klenke, C.: Prognostics/diagnostics for gas turbine engine bearings. In: Proceedings of IEEE Aerospace Conference (2003)
Wang, W., Ismail, F., Golnaraghi, M.: Assessment of gear damage monitoring techniques using vibration measurements. Mechanical Systems and Signal Processing 15(5), 905–922 (2001)
Potter, R., Gribler, M.: Computed order tracking obsoletes older methods. In: Proceedings of SAE Noise and Vibration Conference, pp. 63–67 (1989)
Fyfe, K.R., Munck, E.D.S.: Analysis of computed order tracking. Mechanical Systems and Signal Processing 11(2), 187–205 (1997)
Qian, S.: Gabor expansion for order tracking. Sound and Vibration 37(6), 18–22 (2003)
Vold, H., Leuridan, J.: Resolution order tracking at extreme slow rates, using Kalman tracking filters. In: Proc. SAE Noise and Vibration Conference, Traverse City, MI (1993)
Pan, M.C., Lin, Y.F.: Further exploration of Vold-Kalman-filtering order tracking with shaft-speed information-i: Theoretical part, numerical implementation and parameter investigations. Mechanical Systems and Signal Processing 20, 1134–1154 (2006)
Basseville, M., Le Vey, G.: Analyse et surveillance vibratoire d’une machine en rotation. In: Bensoussan, A., Lions, J., Thoma, M., Wyner, A. (eds.) Analysis and Optimization of Systems. LNCIS, vol. 111. Springer, Heidelberg (1988)
Ypma, A.: Learning methods for machine vibration analysis and health monitoring. PhD thesis, Technische Universiteit Delft (2001)
Staszewski, W., Worden, K.: Signal processing for damage detection. In: Staszewski, W., Boller, C., Tomlinson, G.R. (eds.) Health Monitoring of Aerospace Structures: Smart Sensor Technologies and Signal Processing. Wiley, Chichester (2004)
Feichtinger, H., Strohmer, T.: Gabor analysis and algorithms: theory and applications. Birkhäuser, Boston (1998)
Kraskov, A., Stögbauer, H., Grassberger, P.: Estimating mutual information. Phys. Rev. E 69(6) (2004)
Søndergaard, P.: Finite Discrete Gabor Analysis. PhD thesis, Institut for Matematik - DTU (2007)
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Hazan, A., Verleysen, M., Cottrell, M., Lacaille, J. (2010). Trajectory Clustering for Vibration Detection in Aircraft Engines. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2010. Lecture Notes in Computer Science(), vol 6171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14400-4_28
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DOI: https://doi.org/10.1007/978-3-642-14400-4_28
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