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Vibration and Acoustics Emissions Analysis of Helicopter Gearbox, A Comprative Study

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Book cover Current Trends in Reliability, Availability, Maintainability and Safety

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

This paper investigates the application of signal separation techniques in detection of bearing faults within the epicyclic module of a large helicopter (CS-29) main gearbox using vibration and Acoustic Emissions (AE). It compares their effectiveness for various operating conditions. Three signal processing techniques including an adaptive filter, spectral kurtosis and envelope analysis, were investigated. In addition, this research discusses the feasibility of using AE in helicopter gearbox monitoring.

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References

  1. Chin H, Danai K, Lewicki DG (1993) Pattern classifier for health monitoring of helicopter gearboxes, No. NASA-E-7741, National Aeronautics and Space Administration (NASA) Cleveland OH Lewis Research Center, USA

    Google Scholar 

  2. Zakrajsek JJ (1994) A review of transmission diagnostics research at NASA Lewis Research Center, ARL-TR-599, NASA-TM-106746, E-9158, NAS 1.15:106746, NASA, USA

    Google Scholar 

  3. Chin H, Danai K, Lewicki DG (1993) Efficient fault diagnosis of helicopter gearboxes, (No. NASA-E-7975). National Aeronautics and Space Administration Cleveland OH Lewis Research Center

    Google Scholar 

  4. Decker HJ (2002) Crack detection for aerospace quality spur gears, NASA/TM—2002-211492, ARL-TR-2682. Glenn Research Center, NASA, USA

    Google Scholar 

  5. Zakrajsek JJ, Townsend DP, Decker HJ (1994) An analysis of gear fault detection methods as applied to pitting fatigue failure data. In: The systems engineering approach to mechanical failure prevention, vol 16, Apr 1993. Virginia Beach, Virginia, USA, NASA, USA, pp 199

    Google Scholar 

  6. Pipe K (2002) Measuring the performance of a HUM system-the features that count. In: Third international conference on health and usage monitoring-HUMS2003, pp 5

    Google Scholar 

  7. Samuel PD, Pines DJ (2005) A review of vibration-based techniques for helicopter transmission diagnostics. J Sound Vib 282(1–2):475–508

    Article  Google Scholar 

  8. Decker HJ, Lewicki DG (2003) Spiral bevel pinion crack detection in a helicopter gearbox, NASA/TM—2003-212327—ARL–TR–2958. Glenn Research Center, NASA, USA

    Google Scholar 

  9. Dempsey PJ, Keller JA, Wade DR (2008) Signal detection theory applied to helicopter transmission diagnostic thresholds. In: Proceedings of the American helicopter society 65th annual forum on disc

    Google Scholar 

  10. Cotrell JR (2002) A preliminary evaluation of a multiple-generator drivetrain configuration for wind turbines. In: ASME 2002 wind energy symposium, American Society of Mechanical Engineers, pp. 345

    Google Scholar 

  11. Lynwander P (1983) Gear drive systems: design and application. CRC Press, Florida

    Google Scholar 

  12. Kahraman A (1994) Planetary gear train dynamics. J Mech Des 116(3):713–720

    Article  Google Scholar 

  13. Huang C, Tsai M, Dorrell DG, Lin B (2008) Development of a magnetic planetary gearbox. IEEE Trans Magn 44(3):403–412

    Article  Google Scholar 

  14. Radzevich SP (2012) Dudley’s handbook of practical gear design and manufacture, 2nd edn. CRC press, USA. ISBN 9781439866016

    Google Scholar 

  15. Lu B, Li Y, Wu X, Yang Z (2009) A review of recent advances in wind turbine condition monitoring and fault diagnosis. In: Power electronics and machines in wind applications, 2009, PEMWA 2009. IEEE, p 1

    Google Scholar 

  16. McFadden PD (1987) A revised model for the extraction of periodic waveforms by time domain averaging. Mech Syst Signal Process 1(1):83–95

    Article  Google Scholar 

  17. Randall RB (2004) Detection and diagnosis of incipient bearing failure in helicopter gearboxes. Eng Fail Anal 11(2):177–190

    Article  MathSciNet  Google Scholar 

  18. Wang W (2001) Early detection of gear tooth cracking using the resonance demodulation technique. Mech Syst Signal Process 15(5):887–903

    Article  Google Scholar 

  19. Musial W, Butterfield S, McNiff B (2007) Improving wind turbine gearbox reliability. In: Proceedings of the European wind energy conference

    Google Scholar 

  20. Department for Transport (2011) Report on the accident to aerospatiale (Eurrocopter) AS332 L2 Super Puma, registration G-REDL 11 nm NE of Peterhead, Scotland, on 1 April 2009, 2/2011. Air Accident Investigation Branch, Aldershot

    Google Scholar 

  21. Randall RB, Antoni J (2011) Rolling element bearing diagnostics—a tutorial. Mech Syst Signal Process 25(2):485–520

    Article  Google Scholar 

  22. Howard I (1994) A review of rolling element bearing vibration “detection, diagnosis and prognosis, DSTO-RR-0013, Department of defense

    Google Scholar 

  23. McFadden PD, Toozhy MM (2000) Application of synchronous averaging to vibration monitoring of rolling elements bearings. Mech Syst Signal Process 14(6):891–906

    Article  Google Scholar 

  24. Khemili I, Chouchane M (2005) Detection of rolling element bearing defects by adaptive filtering. Eur J Mech A Solids 24(2):293–303

    Article  MATH  Google Scholar 

  25. Sawalhi N, Randall RB, Forrester D (2014) Separation and enhancement of gear and bearing signals for the diagnosis of wind turbine transmission systems. Wind Energy 17(5):729–743

    Article  Google Scholar 

  26. Antoni J (2005) Blind separation of vibration components: principles and demonstrations. Mech Syst Signal Process 19(6):1166–1180

    Article  Google Scholar 

  27. Bonnardot F, El Badaoui M, Randall RB, Danière J, Guillet F (2005) Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation). Mech Syst Signal Process 19(4):766–785

    Article  Google Scholar 

  28. Qu Y, Van Hecke B, He D, Yoon J, Bechhoefer E, Zhu J (2013) Gearbox fault diagnostics using AE sensors with low sampling rate. J. Acoustic Emission 31:67

    Google Scholar 

  29. Mba D, Rao RB (2006) Development of acoustic emission technology for condition monitoring and diagnosis of rotating machines; bearings, pumps, gearboxes, engines and rotating structures

    Google Scholar 

  30. Holroyd T (2000) Acoustic emission as a basis for the condition monitoring of industrial machinery. In: Proceedings of the 18th Machinery vibration seminar, Canadian Machinery vibration association, pp 27

    Google Scholar 

  31. Ruiz-Cárcel C, Hernani-Ros E, Cao Y, Mba D (2014) Use of spectral kurtosis for improving signal to noise ratio of acoustic emission signal from defective bearings. J Fail Anal Prev 14(3):363–371

    Article  Google Scholar 

  32. Eftekharnejad B, Carrasco M, Charnley B, Mba D (2011) The application of spectral kurtosis on acoustic emission and vibrations from a defective bearing. Mech Syst Signal Process 25(1):266–284

    Article  Google Scholar 

  33. Kilundu B, Chiementin X, Duez J, Mba D (2011) Cyclostationarity of acoustic emissions (AE) for monitoring bearing defects. Mech Syst Signal Process 25(6):2061–2072

    Article  Google Scholar 

  34. Sait A, Sharaf-Eldeen Y (2011) A review of gearbox condition monitoring based on vibration analysis techniques diagnostics and prognostics. In: Proulx T (ed) Rotating machinery, structural health monitoring, shock and vibration, vol 5. Springer, New York, pp 307–324. ISBN 978-1-4419-9427-1

    Google Scholar 

  35. Martin HR (1989) Statistical moment analysis as a means of surface damage detection. In: Proceeding of the 7th international model analysis conference, society of experimental mechanics, pp 1016–1021

    Google Scholar 

  36. Mehala N, Dahiya R (2008) A comparative study of FFT, STFT and wavelet techniques for induction machine fault diagnostic analysis. In: Proceedings of the 7th WSEAS international conference on computational intelligence, man-machine systems and cybernetics. Cairo, Egypt, World Scientific and Engineering Academy and Society, WSEAS; Stevens Point, Wisconsin, USA, pp 203

    Google Scholar 

  37. Wang WJ, McFadden PD (1996) Application of wavelets to gearbox vibration signals for fault detection. J Sound Vib 192(5):927–939

    Article  Google Scholar 

  38. Wang WJ, McFadden PD (1993) Early detection of gear failure by vibration analysis i. calculation of the time-frequency distribution. Mech Syst Signal Process 7(3):193–203

    Article  Google Scholar 

  39. Elasha F, Ruiz-Carcel C, Mba D, Chandra P (2014) A comparative study of the effectiveness of adaptive filter algorithms, spectral kurtosis and linear prediction in detection of a naturally degraded bearing in a gearbox. J Fail Anal Prev 14:1–14

    Google Scholar 

  40. Elasha F, Mba D, Ruiz-Carcel C (2015) Effectiveness of adaptive filter algorithms and spectral kurtosis in bearing faults detection in a gearbox. In: Sinha JK (ed) Springer International Publishing, pp 219–229. ISBN 978-3-319-09917-0

    Google Scholar 

  41. Yu L, Momeni S, Godinez V, Giurgiutiu V (2011) Adaptation of PWAS transducers to acoustic emission sensors. In: SPIE smart structures and materials nondestructive evaluation and health monitoring. International Society for Optics and Photonics, pp 798327

    Google Scholar 

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Acknowledgement

The Work described in this paper was conducted as part of EASA.2012.OP.13 VHM. The support of Airbus Helicopters in full-scale testing id gratefully acknowledged.

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Correspondence to Faris Elasha .

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Elasha, F., Mba, D. (2016). Vibration and Acoustics Emissions Analysis of Helicopter Gearbox, A Comprative Study. In: Kumar, U., Ahmadi, A., Verma, A., Varde, P. (eds) Current Trends in Reliability, Availability, Maintainability and Safety. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-23597-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-23597-4_10

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