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Condition monitoring of naturally damaged slow speed slewing bearing based on ensemble empirical mode decomposition

Journal Article


Abstract


  • There have been extensive studies on vibration based condition monitoring, prognosis of rotating element bearings; and reviews of the

    methods on how to identify bearing fault and predict the final failure reported widely in literature. The investigated bearings commonly

    discussed in the literatures were run in moderate and high rotating speed, and damages were artificially introduced e.g. with artificial

    crack or seeded defect. This paper deals with very low rotational-speed slewing bearing (1-4.5 rpm) without artificial fault. Two real

    vibration data were utilized, namely data collected from lab slewing bearing subject to accelerated life test and from a sheet metal company.

    Empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) were applied in both lab slewing

    bearing data and real case data. Outer race fault (BPFO) and rolling element fault (BSF) frequencies of slewing bearing can be identified.

    However, these fault frequencies could not be identified using fast Fourier transform (FFT).

Authors


  •   Caesarendra, Wahyu (external author)
  •   Kosasih, Buyung B.
  •   Tieu, A Kiet.
  •   Moodie, Craig A. S. (external author)
  •   Choi, Byeongkeun (external author)

Publication Date


  • 2013

Citation


  • Caesarendra, W., Kosasih, P., Tieu, A. Kiet., Moodie, C. Alexander Simpson. & Choi, B. (2013). Condition monitoring of naturally damaged slow speed slewing bearing based on ensemble empirical mode decomposition. Journal of Mechanical Science and Technology, 27 (8), 2253-2262.

Scopus Eid


  • 2-s2.0-84884504255

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1384

Has Global Citation Frequency


Number Of Pages


  • 9

Start Page


  • 2253

End Page


  • 2262

Volume


  • 27

Issue


  • 8

Place Of Publication


  • Germany

Abstract


  • There have been extensive studies on vibration based condition monitoring, prognosis of rotating element bearings; and reviews of the

    methods on how to identify bearing fault and predict the final failure reported widely in literature. The investigated bearings commonly

    discussed in the literatures were run in moderate and high rotating speed, and damages were artificially introduced e.g. with artificial

    crack or seeded defect. This paper deals with very low rotational-speed slewing bearing (1-4.5 rpm) without artificial fault. Two real

    vibration data were utilized, namely data collected from lab slewing bearing subject to accelerated life test and from a sheet metal company.

    Empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) were applied in both lab slewing

    bearing data and real case data. Outer race fault (BPFO) and rolling element fault (BSF) frequencies of slewing bearing can be identified.

    However, these fault frequencies could not be identified using fast Fourier transform (FFT).

Authors


  •   Caesarendra, Wahyu (external author)
  •   Kosasih, Buyung B.
  •   Tieu, A Kiet.
  •   Moodie, Craig A. S. (external author)
  •   Choi, Byeongkeun (external author)

Publication Date


  • 2013

Citation


  • Caesarendra, W., Kosasih, P., Tieu, A. Kiet., Moodie, C. Alexander Simpson. & Choi, B. (2013). Condition monitoring of naturally damaged slow speed slewing bearing based on ensemble empirical mode decomposition. Journal of Mechanical Science and Technology, 27 (8), 2253-2262.

Scopus Eid


  • 2-s2.0-84884504255

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1384

Has Global Citation Frequency


Number Of Pages


  • 9

Start Page


  • 2253

End Page


  • 2262

Volume


  • 27

Issue


  • 8

Place Of Publication


  • Germany