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Research Papers

Approximate Entropy Analysis of the Acoustic Emission From Defects in Rolling Element Bearings

[+] Author and Article Information
Yongyong He

e-mail: heyy@mail.tsinghua.edu.cn

Xinming Zhang

The State Key Laboratory of Tribology,
Tsinghua University,
Beijing 100084, People's Republic of China

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the Journal of Vibration and Acoustics. Manuscript received April 25, 2011; final manuscript received May 4, 2012; published online October 29, 2012. Assoc. Editor: Thomas J. Royston.

J. Vib. Acoust 134(6), 061012 (Oct 29, 2012) (8 pages) doi:10.1115/1.4007240 History: Received April 25, 2011; Revised May 04, 2012

This paper introduces approximate entropy (ApEn) to address a nonlinear feature parameter of acoustic emission (AE) signal for the defect detection of rolling element bearings. With respect to AE signal, parameter selection of ApEn calculation is investigated, and appropriate parameters are suggested. Finally, an experimental study is presented to investigate the influence of various running conditions, i.e., radial load, rotating speed and defect size, on ApEn calculation. The results demonstrate that ApEn provides an effective measure for AE analysis and can be used as an effective feature parameter of AE signal for the defect detection of rolling element bearings.

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References

Figures

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Fig. 1

Simulation AE signal and its calculated ApEn values by different parameters: (a) simulation AE signal; (b) the calculated ApEn values by different parameters

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Fig. 2

Lead-breaking AE signal and its calculated ApEn values by different parameters: (a) lead-breaking AE signal; (b) the calculated ApEn values by different parameters

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Fig. 3

Influence of white noise on ApEn

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Fig. 4

Experimental test rig

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Fig. 5

Collected AE signals from four conditions: (a) condition (L0, S1, D0); (b) condition (L1, S1, D1); (c) condition (L1, S2, D2); (d) condition (L2, S3, D2)

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Fig. 6

Corresponding de-noised AE signals: (a) condition (L0, S1, D0); (b) condition (L1, S1, D1); (c) condition (L1, S2, D2); (d) condition (L2, S3, D2)

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Fig. 7

White noise and its de-noised signal: (a) white noise; (b) de-noised white noise; (c) the spectrum of signal in Fig. 5(a)

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Fig. 8

Spectrum comparison of de-noised signals: (a) condition (L0, S1, D0); (b) condition (L1, S1, D1)

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Fig. 9

Comparison of de-noised AE signals within one period: (a) condition (L0, S1, D0); (b) condition (L1, S1, D1)

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Fig. 10

ApEn comparison of AE signals from different defect sizes

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Fig. 11

ApEn comparison of AE signals from undamaged bearing

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Fig. 12

ApEn comparison of AE signals from different rotating speeds

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Fig. 13

ApEn comparison of AE signals from radial loads

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