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A Novel Condition Indicator for Bearing Fault Detection Within Helicopter Transmission

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Journal of Vibration Engineering & Technologies Aims and scope Submit manuscript

Abstract

Background

Helicopter usage and monitoring system (HUMS) is one of the critical systems for helicopter’s safety and reliability. Whilst HUMS has proven to be effective in detecting gears’ defects, bearing failures are not adequately detected using current monitoring indicators. Detection of bearing faults in helicopter gearboxes is made challenging by the presence of the complicated signal transmission path attenuating the monitored signal to the receiving sensor.

Purpose

To ensure safe operation of helicopters, this research proposes a novel condition indicator to detect bearing faults in helicopter gearboxes.

Methods

For this purpose, vibration measurements captured from a CS-29 category ‘A’ helicopters test rig were utilized for detecting a bearing defect that has occurred in the epicyclic module of the main gearbox. Signals of rolling element bearings under various fault conditions were collected, and an adaptive filter algorithm was utilized to separate the random component of the signal. The resultant signatures were then further processed using wavelet analysis to extract the bearing signal of interest.

Results

Results showed that this new indicator successfully detect bearing faults. Besides, the impulse energy indicator responds consistently to the fault severity compared to the traditional indicators such as RMS and kurtosis.

Conclusion

A technique to extract frequency band corresponding to the bearing fault impulses has been developed and tested. The technique employs the adaptive filter signal separation, wavelet packet decomposition and the combination of RMS and kurtosis to select the optimum filter band.

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Acknowledgements

This study is sponsored by European Aviation Safety Agency (EASA), project entitled “MGH—Helicopter main gearbox health”.

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Authors and Affiliations

  1. Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK

    Faris Elasha

  2. Faculty of Technology, De Montfort University, Leicester, UK

    Xiaochuan Li & David Mba

  3. Department of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, China

    David Mba

  4. Department of Mechanical Engineering, University of Lagos, Nsukka, Nigeria

    Adebayo Ogundare & Sunday Ojolo

Authors
  1. Faris Elasha
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  2. Xiaochuan Li
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  3. David Mba
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  4. Adebayo Ogundare
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  5. Sunday Ojolo
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Correspondence to Faris Elasha.

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Elasha, F., Li, X., Mba, D. et al. A Novel Condition Indicator for Bearing Fault Detection Within Helicopter Transmission. J. Vib. Eng. Technol. 9, 215–224 (2021). https://doi.org/10.1007/s42417-020-00220-7

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  • DOI: https://doi.org/10.1007/s42417-020-00220-7

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