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Wear failure analysis of ball bearings based on lubricating oil for gas turbine

Wear failure analysis of ball bearings based on lubricating oil for gas turbine Ball bearings in gas turbine have played a critical role in supporting heavy radial loads but with higher failure rates and repair costs. Therefore, the purpose of this study is to introduce and study a method for their failure analysis with an actual industrial example to guarantee operation reliability and safety.Design/methodology/approachSpectrometric oil analysis was used as an early abnormal wear indicator, based on which emergent in-use oil replacement was carried out to reduce the wear rate. However, with wear deterioration, further wear failure investigation was conducted by LaserNet Fines and ferrography to detect the imminent wear failure. Finally, with the assistance of elemental analysis of the typical wear particles, the root cause and worn components were determined by scanning electronic microscope and energy-dispersive X-ray spectroscopy.FindingsThe results have shown that an extraneous source led to wear failure, which later caused overheat between the outer bearing ring and ball. It is in accordance with visual inspection of the disassembled engine.Originality/valueThis method has specified the occasion under which the suitable measurement can be taken. It can achieve the rapid wear condition assessment allowing for root cause and worn parts identification. In addition, wear rate reduction by change of oil can be efficient for most of the time to avoid premature disassemble, especially with the possibility of contamination. It has provided experience to address similar industry-level practical wear failure analysis problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Lubrication and Tribology Emerald Publishing

Wear failure analysis of ball bearings based on lubricating oil for gas turbine

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0036-8792
eISSN
0036-8792
DOI
10.1108/ilt-04-2022-0151
Publisher site
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Abstract

Ball bearings in gas turbine have played a critical role in supporting heavy radial loads but with higher failure rates and repair costs. Therefore, the purpose of this study is to introduce and study a method for their failure analysis with an actual industrial example to guarantee operation reliability and safety.Design/methodology/approachSpectrometric oil analysis was used as an early abnormal wear indicator, based on which emergent in-use oil replacement was carried out to reduce the wear rate. However, with wear deterioration, further wear failure investigation was conducted by LaserNet Fines and ferrography to detect the imminent wear failure. Finally, with the assistance of elemental analysis of the typical wear particles, the root cause and worn components were determined by scanning electronic microscope and energy-dispersive X-ray spectroscopy.FindingsThe results have shown that an extraneous source led to wear failure, which later caused overheat between the outer bearing ring and ball. It is in accordance with visual inspection of the disassembled engine.Originality/valueThis method has specified the occasion under which the suitable measurement can be taken. It can achieve the rapid wear condition assessment allowing for root cause and worn parts identification. In addition, wear rate reduction by change of oil can be efficient for most of the time to avoid premature disassemble, especially with the possibility of contamination. It has provided experience to address similar industry-level practical wear failure analysis problems.

Journal

Industrial Lubrication and Tribology – Emerald Publishing

Published: Jan 2, 2023

Keywords: Wear failure; Ball bearings; Lubricating oil; Gas turbine; Ferrography

References

  • Generation of wear particles and running-in mixed lubricated sliding contacts
    Akchurin, A.; Bosman, R.; Lugt, P.M.
  • Characterization of white etching crack damage in wind turbine gearbox bearings
    Bruce, T.; Rounding, E.
  • Prediction of wear trend of engines via on-line wear debris monitoring
    Cao, W.; Dong, G.; Xie, Y.B.; Peng, Z.
  • An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems
    Deng, W.; Zhang, X.; Zhou, Y.; Liu, Y.; Zhou, X.; Chen, H.; Zhao, H.
  • Inductive coulter counting: detection and differentiation of metal wear particles in lubricants
    Du, L.; Zhe, J.
  • Computational fatigue analysis of contacting mechanical elements
    Fajdiga, G.
  • An adhesion-dominated rolling friction regime unique to micro-scale ball bearings
    Hanrahan, B.; Misra, S.; Beyaz, M.I.; Feldman, J.H.; Waits, C.M.; Ghodssi, R.
  • A study on the rotor profile and internal clearances of the Gerotor pump used in lubricating system of gas turbine engine
    Hussain, T.; Sarangi, N.
  • Metallurgical analysis of the surface distress on balls during the operation of AISI 440C ball bearings for satellite applications
    Jalaja
  • An object detection network for wear debris recognition in ferrography images
    Jia, F.G.; Wei, H.; Sun, H.; Song, L.; Yu, F.
  • Failure analysis of blades and vanes of a compressor for a gas turbine engine
    Kwon, H.; Lee, D.
  • Morphological and chemical compositions of wear debris naturally formed in grease lubricated railway axle bearings
    Lin, C.; Meehan, P.A.
  • Research and evaluation on wear in power-shift steering transmission through oil spectral analysis with RKPCA method
    Liu, Y.; Ma, B.; Zheng, C.S.; Li, S.C.
  • A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings
    Liu, Z.P.; Zhang, L.
  • Wear particle analysis utilization of quantitative computer image analysis – a review
    Raadnui, S.
  • Review on gas turbine condition based on diagnosis method
    Salilew, W.; Karim, Z.K.
  • Watershed-based morphological separation of wear debris chains for on-line ferrograph analysis
    Wu, H.K.; Wu, T.H.
  • Steam turbine blade failure analysis
    Zdzisiaw, M.; Garcia-Illescas, R.; Aguirre-Romano, J.; Perez-Rodriguez, N.
  • Electron microscopy analysis of structural changes within white etching areas
    Diederichs, A.M.; Schwedt, A.; Mayer, J.; Dreifert, T.
  • Parallel sensing of metallic wear debris in lubricants using under sampling
    Du, L.; Zhe, J.
  • Material wear and fatigue in wind turbine systems
    Greco, A.; Sheng, S.; Keller, J.; Erdemir, A.