Abstract
Helicopters have been extensively employed as a versatile tool in modern society, thus guaranteeing operation safety and flightworthiness has always been our top-tier concerns. However, many accidents indicate that current helicopter health and usage monitoring system (HUMS) are not accurate and effective enough to fulfil this goal, especially for detecting an imminent planetary bearing fault (CAA Authority 2006). To study this case and address such issues, an experiment was undertaken with a special rig, comprising of real helicopter main gearbox (MGB) and dynamometer as a variable load. Defects of different sizes were seeded at the outer race of bearings inside second epicyclic planetary module. Vibration signals of different test conditions (input speed, load and defect sizes) were recorded for post-processing. Measured vibration data contains overwhelming background noise and planetary gear meshes, making it cumbersome to identify the bearing defect. Various signal processing techniques are applied to identify the bearing defect, including signal pre-whitening, gear/bearing signal separation, kurtogram, envelope analysis, high-order spectral analysis and so on. The comparative results suggest that certain combinations of aforementioned methods are more effective than single process techniques. One case of successful detection is demonstrated in this paper. This study potentially benefits improving HUMS effectiveness and supports helicopter maintenance decision-making.
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References
Accident Investigation Board Norway (2016) Preliminary report on accident at Turoy, near Bergen, Norway on 29 April 2016, involving airbus helicopters h225, LN-OJF. https://www.aibn.no/Aviation/Investigations
Antoni J, Randall RB (2004a) Unsupervised noise cancellation for vibration signals: Part I—evaluation of adaptive algorithms. Mech Syst Signal Process 18(1):89–101
Antoni J, Randall RB (2004b) Unsupervised noise cancellation for vibration signals: Part II—a novel frequency-domain algorithm. Mech Syst Signal Process 18(1):103–117
Authority CA (2006) CAP 753Helicopter vibration health monitoring (VHM) guidance material for operators utilizing VHM in rotor and rotor drive systems of helicopters, 1st edn
Bechhoefer E, Kingsley M (2009) A review of time synchronous average algorithms. In: Annual conference of the prognostics and health management society, San Diego, CA, pp 24–33
Bogert BP, Healy MJ, Tukey JW (1963) The quefrency alanysis of time series for echoes: cepstrum, pseudo-autocovariance, cross-cepstrum and saphe cracking. In: Proceedings of the symposium on time series analysis, vol 15, pp 209–243
Bonnardot F, El Badaoui M, Randall RB, Daniere 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
Borghesani P, Pennacchi P, Randall, RB, Sawalhi N, RicciR (2013) Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions. Mech Syst Signal Process 36(2):370–384
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. Air Accident Investigation Branch, Aldershot, UK, 2/2011
Fyfe KR, Munck ED (1997) Analysis of computed order tracking. Mech Syst Signal
Greaves M, Elasha F, Mba D et al (2013) VHM vibration health or alternative monitoring technologies for helicopters, EASA.2012.OP.13, UK
International Helicopter Team (2013) Health and usage monitoring system toolkit. http://www.ihst.org/portals/54/Toolkit_HUMS.pdf
Land JE (2001) HUMS—the benefits-past, present and future. In: Aerospace conference, 2001, IEEE proceedings, vol 6. IEE, pp 3083–3094
Larder AD (1999) Helicopter HUM/FDR: benefits and developments. In: Annual forum proceedings—American Helicopter, vol 55. American Helicopter Society, pp 1839–1846
Mba D, Place S, Rashid H, Lim CK (2011) Helicopter main gearbox loss of oil performance optimization—HELMGOP. Final report No. EASA, 5
McFadden PD, Toozhy MM (2000) Application of synchronous averaging to vibration monitoring of rolling element bearings. Mech Syst Signal Process 14(6):891–906
Randall RB (2016) A history of cepstrum analysis and its application to mechanical problems. Mech Syst Signal Process
Randall RB, Antoni J (2011) Rolling element bearing diagnostics—a tutorial. Mech Syst Signal Process 25(2):485–520
Randall RB, Smith WA (2016) New cepstral methods for the diagnosis of gear and bearing faults under variable speed conditions. In: ICSV23 conference, Athens
Selesnick IW, Baraniuk RG, Kingsbury NC (2005) The dual-tree complex wavelet transform. IEEE Signal Process Mag 22(6):123–151
Večeř P, Kreidl M, Šmíd R (2005) Condition indicators for gearbox condition monitoring systems. ActaPolytechnica 45(6)
Wang Y, He Z, Zi Y (2010) Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform. Mech Syst Signal Process 24(1):119–137
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Zhou, L., Duan, F., Faris, E., Mba, D. (2018). Seeded Planetary Bearing Fault in a Helicopter Gearbox—A Case Study. In: Haddar, M., Chaari, F., Benamara, A., Chouchane, M., Karra, C., Aifaoui, N. (eds) Design and Modeling of Mechanical Systems—III. CMSM 2017. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-66697-6_48
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DOI: https://doi.org/10.1007/978-3-319-66697-6_48
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