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Solid lubricated bearings performance degradation assessment: A fuzzy self-organizing map method

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Warianty tytułu
PL
Ocena obniżenia charakterystyk łożysk ze smarem stałym: metoda rozmytych samoorganizujących się map
Języki publikacji
EN
Abstrakty
EN
Solid lubricated bearings are common components in space mechanisms, and their reliability and performance degradation assessment are very crucial. In this study, a fuzzy self-organizing map method is used to perform performance degradation assessment. Feature vectors are constructed by indices of vibration as well as friction torque signal. Self-organizing map is then used to perform performance degradation assessment and the subjection of each feature vector to normal cluster on output layer is used as degradation indicator. Accelerated life test results show that this method can make effective performance degradation assessment and describe degradation degree in the whole life time.
PL
Łożyska ze smarem stałym to powszechnie stosowane elementy urządzeń, a ich niezawodność i ocena degradacji charakterystyk są bardzo istotne. W przedstawionej pracy wykorzystano metodę rozmytych samoorganizujących się map do oceny obniżenia charakterystyk. Wektory cech skonstruowano za pomocą wskaźników wibracji, jak również sygnału momentu tarcia. Następnie dokonano oceny obniżenia charakterystyk z wykorzystaniem samoorganizującej się mapy, a za wskaźnik degradacji przyjęto przynależność każdego wektora cech do normalnej grupy w warstwie wyjściowej. Wyniki badań przyspieszonych pokazują, że przy użyciu omawianej metody można dokonywać skutecznej oceny obniżenia charakterystyk a także opisywać stopień degradacji w całym okresie eksploatacji.
Rocznik
Strony
397--402
Opis fizyczny
Bibliogr, 33 poz., rys., tab.
Twórcy
autor
  • School of Automation Science and Electrical Engineering Beihang University No. 37 Xueyuan Road, Haidian District, Beijing, China, 100191
autor
  • School of Automation Science and Electrical Engineering Beihang University No. 37 Xueyuan Road, Haidian District, Beijing, China, 100191
Bibliografia
  • 1. Bauer R, Fleischauer P. Torque characteristics of solid-lubricated precision bearings during oscillatory motion. Los Angeles: Space and Missile Systems Center Air Force Materiel Command; 1994.
  • 2. Finkin EF. Theoretical-Analysis of Factors Controlling the Wear of Solid-Film-Lubricated Ball-Bearings. Wear 1984; 94 (2): 211–7.
  • 3. Fusaro R, Jansen M. Preventing Spacecraft Failures Due to Tribological Problems. Orlando: NASA; 2001.
  • 4. Gupta PK. Some Dynamic Effects in High-Speed Solid-Lubricated Ball-Bearings. Asle Transactions 1983; 26(3): 393–400.
  • 5. Gupta PK, Dill JF, Bandow HE. Parametric Evaluation of a Solid-Lubricated Ball-Bearing. Asle Transactions 1985; 2 8 (1): 31–9.
  • 6. Gupta PK, Forster NH. Modeling of Wear in a Solid-Lubricated Ball-Bearing. Asle Transactions 1987; 30 (1): 55–62.
  • 7. Hiraoka N. Wear life mechanism of journal bearings with bonded MoS2 film lubricants in air and vacuum. Wear 2001; 249 (10–11): 1014–20.
  • 8. Huang RQ, Xi LF, Li XL, Liu CR, Qiu H, Lee J. Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods. Mechanical Systems and Signal Processing 2007; 21 (1): 193–207.
  • 9. Jones W, Jansen M. Lubrication for Space Applications. Cleveland: NASA; 2005.
  • 10. Kohonen T. Self-Organizing Maps. Springer; 1995.
  • 11. Lee J. Measurement of machine performance degradation using a neural network model. Computers in Industry 1996; 30 (3): 193–209.
  • 12. Lin J, Zuo MJ. Gearbox fault diagnosis using adaptive wavelet filter. Mechanical Systems and Signal Processing 2003; 17 (6):1 259–69.
  • 13. Mayer R, Rauber A. Visualising Clusters in Self-Organising Maps with Minimum Spanning Trees. Artificial Neural Networks-Icann 2010, Pt Ii 2010; 6353: 426–31.
  • 14. Mcfadden PD, Smith JD. Vibration Monitoring of Rolling Element Bearings by the High-Frequency Resonance Technique – a Review.Tribology International 1984; 17(1): 3–10.
  • 15. Meeks CR, Bohner J. Predicting Life of Solid-Lubricated Ball-Bearings. Asle Transactions 1986; 29(2): 203–13.
  • 16. Murray F, Heshmat H, Fusaro R. Accelerated testing of space mechanisms. Cleveland: NASA; 1995.
  • 17. Nishimura M, Suzuki M. Solid-lubricated ball bearings for use in a vacuum state – state of-the-art. Tribology International 1999; 32 (11):637–47.
  • 18. Ocak H, Ertunc HM, Loparo KA. Online tracking of bearing wear using wavelet packet transform and hidden Markov models. 2006 IEEE 14th Signal Processing and Communications Applications, Vols 1 and 2 2006: 137–40.
  • 19. Ocak H, Loparo KA, Discenzo FM. Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics. Journal of Sound and Vibration 2007; 302 (4–5): 951–61.
  • 20. Pan Y, Chen J, Guo L. Robust bearing performance degradation assessment method based on improved wavelet packet-support vector data description. Mechanical Systems and Signal Processing 2009; 23 (3): 669–81.
  • 21. Qiu H, Lee J, Lin J, Yu G. Robust performance degradation assessment methods for enhanced rolling element bearing prognostics. Advanced Engineering Informatics 2003; 17 (3-4): 127–40.
  • 22. Rapoport L, Moshkovich A, Perfilyev V, Lapsker I, Halperin G, Itovich Y, Etsion I. Friction and wear of MoS(2) films on laser textured steel surfaces. Surface & Coatings Technology 2008; 202 (14):3332–40.
  • 23. Saito T, Naka M, Ito H, Yamamoto T, Matsunaga S. Particle generation by solid-lubricated bearings and ball screws in vacuum environments. Tribology Transactions 1999; 42 (1): 162–7. 24. Tandon N, Choudhury A. A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International 1999; 32 (8): 469–80. 25. Todd MJ. Modeling of Ball-Bearings in Spacecraft. Tribology International 1990; 23 (2): 123–8.
  • 26. Todd MJ. Solid Lubrication of Ball-Bearings for Spacecraft Mechanisms. Tribology International 1982; 15 (6): 331–7.
  • 27. Todd MJ, Johnson KL. A Model for Coulomb Torque Hysteresis in Ball-Bearings. International Journal of Mechanical Sciences 1987; 29 (5): 339–54.
  • 28. Wang L, Jiang MH, Lu YH, Noe F, Smith JC. Self-organizing map clustering analysis for molecular data. Advances in Neural Networks – Isnn 2006, Pt 1 2006; 3971: 1250–5.
  • 29. Xu GH, Lee JH, Hong L. Low-temperature tribological properties of solid lubricating coatings. Contributions of Surface Engineering to Modern Manufacturing and Remanufacturing 2002: 357–62.
  • 30. Xu GZH, Lee JH, Liang H, Georing D. Tribological properties of solid-lubricating coatings on cylinder bore at low temperature. Wear 2004; 257 (1–2): 59–65.
  • 31. Yiakopoulos CT, Antoniadis IA. Wavelet based demodulation of vibration signals generated by defects in rolling element bearings. Shock and Vibration 2002; 9 (6): 293–306.
  • 32. Yu JB. Bearing performance degradation assessment using locality preserving projections. Expert Systems with Applications 2011; 38 (6): 7440–50.
  • 33. Yu JB. Bearing performance degradation assessment using locality preserving projections and Gaussian mixture models. Mechanical Systems and Signal Processing 2011; 25 (7): 2573–88.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5e635d49-5f7d-4cf5-a2eb-cfe8a3b6f4db
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