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Comparison of rolling bearings’ diagnosing methods - procedures of damage introduction

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The rolling bearings’ diagnosing methods used in exploitation diagnostics are not usually dedicated to the postproduction control. However, this does not mean, that they cannot be used there. A comprehensive comparison of the sensitivity of rolling bearings’ diagnosing methods to occurrence of faults and damage should be based on measurements of new, undamaged bearings and bearings with defects. An accurate determination of the location, size and origin of defects is expected from a set of testing bearings. The paper presents a comparison of three methods of damage introduction: sandblasting, pickling and spark erosion. Procedures for introducing damage into bearing’s races have been described. In addition, race’s geometries and vibration signals generated by operating bearings were compared.
Rocznik
Tom
Strony
art. no. 2018011
Opis fizyczny
Bibliogr. 24 poz., il. kolor., fot., wykr.
Twórcy
autor
  • Poznan University of Technology, Faculty of Mechanical Engineering and Management, 3 Piotrowo St, 60-965 Poznan
  • Poznan University of Technology, Faculty of Mechanical Engineering and Management, 3 Piotrowo St, 60-965 Poznan
autor
  • Poznan University of Technology, Faculty of Chemical Technology, 4 Berdychowo St, 60-101 Poznan
Bibliografia
  • 1. S. Radkowski, Diagnozowanie Łożysk Tocznych in Inżynieria Diagnostyki Maszyn Ed. B. Żółtowski, C. Cempel, Polskie Towarzystwo Diagnostyki Technicznej Instytut Technologii Eksploatacji - PIB, Radom 2004, 529 - 544.
  • 2. R. B. Randall, J. Antoni, Rolling element bearing diagnostics—A tutorial, Mechanical Systems and Signal Processing, 25 (2010) 485 - 520.
  • 3. R. B. Randal, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications, Wiley, New Delhi 2011, 200 - 202.
  • 4. C. Cempel, Podstawy wibroakustycznej diagnostyki maszyn, Wydawnictwo Naukowo Techniczne, Warszawa 1982, 156 - 177.
  • 5. B. T. Holm-Hansen, R. X. Gao, L. Zhang, Customized Wavelet for Bearing Defect Detection, Transactions of the ASME, 126 (2004) 740 - 745.
  • 6. N. Tandon, A. Choudhury, A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings, Tribology International, 32 (1999) 469 - 480.
  • 7. T. Williams, X, Ribadeneira, S. Billington et al., Rolling Element Bearing Diagnostics In Run-To-Failure Lifetime Testing, Mechanical Systems and Signal Processing, 15 (2001) 979 - 993.
  • 8. D. E. Butler, The Shock-pulse method for the detection of damaged rolling bearings, Non-Destructive Testing, 6 (1973) 92 - 95.
  • 9. G. Allenby, Condition based maintenance in Condition Monitoring and Diagnostic Engineering Management Ed. R. Rao, Chapman and Hall, Padstow 1990, 155 - 161.
  • 10. F. Xi, Q. Qiao Sun, G. Krishnappa, Bearing Diagnostics Based on Pattern Recognition of Statistical Parameters, Journal of Vibration and Control, 6 (2000) 375 - 392.
  • 11. R. G. Harker, J. S. Hansen, Rolling element bearing monitoring using high gain eddy current transducers, Journal of Engineering for Gas Turbines, 107 (1985) 160 - 164.
  • 12. D. E. Bently, P. Goldman, J. J. Yu, Rolling Element Bearing Defect Detection and Di-agnostics Using REBAM Probes, Orbit 2001, 12 - 25.
  • 13. B. Li, M. Y. Chow, Y. Tipsuwan et al. Neural-Network-Based Motor Rolling Bearing Fault Diagnosis, IEEE Transactions On Industrial Electronics, 47 (2000) 1060 - 1068.
  • 14. I. E. Alguindigue, A. Loskiewicz-Buczak, R. E. Uhrig, Monitoring and Diagnosis of Rolling Element Bearings Using Artificial Neural Networks, IEEE Transactions On Industrial Electronics, 40 (1993) 209 - 217.
  • 15. A. Gałęzia, R. Barczewski, B. Jakubek, Possibilities of faults detection of rolling bearings using energetic descriptors of vibrations signals, Advances in Condition Monitoring of Machinery in Non-Stationary Operations: Proceedings of the 5th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, Springer, 2018, 329 - 328.
  • 16. M. Liang, B. I. Soltani, An energy operator approach to joint application of amplitude and frequency-demodulation for bearing fault detection, Mechanical Systems and Signal Processing, 24 (2010) 1473 - 1494.
  • 17. R. P. Henríquez, J. B. Alonso, M. A. Ferrer, et al. Application of the Teager-Kaiser energy operator in bearing fault diagnosis. ISA Transactions, 52 (2013) 278 - 284.
  • 18. I. Antoniadou, T. P. Howard, R. S. Dwyer-Joyce, et al. Envelope Analysis Using the Teager-Kaiser Energy Operator for Condition Monitoring of a Wind Turbine Bearing, Applied Mechanics and Materials, 564 (2014) 170 - 175.
  • 19. J. Dybała, R. Zimroz, Rolling bearing diagnosing method based on Empirical Mode Decomposition of machine vibration signal, Applied Acoustics, 77 (2014) 195 - 203.
  • 20. H. Madej, Z. Stanik, J. Warczek, The vibroacoustic methods and their application in the diagnostics of the combustion engines’s roller-bearing fittings, Journal of KONES Powertrain and Transport, 17 (2010) 293 - 297.
  • 21. ISO 15242-1(2015) Rolling bearings - Measuring methods for vibration - Part 1: Fundamentals.
  • 22. T. Burakowski, T. Wierzchoń, Inżynieria powierzchni metali, Wydawnictwo Naukowo Techniczne, Warszawa 1995, 68 - 70.
  • 23. N. N. Greenwood, A. Earnshaw, Chemistry of the Elements, Butterworth-Heinemann, 1997, 946 - 948.
  • 24. B. Jakubek, R. Barczewski, M. Jakubowicz, The influence of the lubrication on the vibroacoustic signal generated by rolling bearings, Journal of Vibrations in Physical Systems, 28 (2017) 1 - 9.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a8f38145-9fef-46f5-8aa7-324ba6369a4d
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