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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

Tandon, N., and Nakra, B. C., 1992, “Vibration and Acoustic Monitoring Technique for the Detection of Defects in Rolling Element Bearings—A Review,” Shock Vib., 24, pp. 3–11. [CrossRef]
Tandon, N., and Choudhury, A., 1999, “A Review of Vibration and Acoustic and Acoustic Measurement Methods for the Detection of Defects in Rolling Element Bearing,” Tribol. Int., 32, pp. 469–480. [CrossRef]
Behzad, M., AlandiHallaj, A., Rohani Bastami, A., Mba, D., Eftekharnejad, B., and Charnley, B., 2009, “Defect Size Estimation in Rolling Element Bearings Using Vibration Time Waveform,” Insight, 51(8), pp. 426–430. [CrossRef]
Tse, P. W., Peng, Y. H., and Yam, R., 2011, “Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities,” Trans. ASME, J. Vib. Acoust., 123, pp. 303–310. [CrossRef]
Ono, K., and Okada, Y., 1998, “Analysis of Ball Bearing Vibrations Caused by Outer Race Waviness,” Trans. ASME, J. Vib. Acoust., 120, pp. 901–908. [CrossRef]
He, Y., Zhang, X., and Friswell, M. I., 2009, “Defect Diagnosis for Rolling Element Bearings Using Acoustic Emission,” Trans. ASME, J. Vib. Acoust., 131(6), p. 061012. [CrossRef]
Balerston, H. L., 1996, “The Detection of Incipient Failure in Bearings,” Mater. Eval., 27, pp. 121–128.
Mba, D., Raj, B. K., and Rao, N., 2006, “Development of Acoustic Emission Technology for Condition Monitoring and Diagnosis of Rotating Machines: Bearings, Pumps, Gearboxes, Engines, and Rotating Structures,” Shock Vib. Dig., 38, pp. 3–16. [CrossRef]
Price, E. D., Lees, A. W., and Friswell, M. I., 2005, “Detection of Severe Sliding and Pitting Fatigue Wear Regimes Through the Use of Broadband Acoustic Emission,” J. Eng. Tribol., 219, pp. 85–98. [CrossRef]
Morhain, A., and Mba, D., 2003, “Bearing Defect Diagnosis and Acoustic Emission,” J. Eng. Tribol., 217, pp. 257–272. [CrossRef]
Elforjani, M., and Mba, D., 2008, “Detecting the Onset, Propagation and Location of Non-Artificial Defects in a Slow Rotating Thrust Bearing With Acoustic Emission,” Insight, 50(5), pp. 264–268. [CrossRef]
Al-Ghamdi, A. M., Cole, P., Such, R., and Mba, D., 2004, “Estimation of Bearing Defect Size With Acoustic Emission,” Insight, 46(12), pp. 758–761. [CrossRef]
Rao, S. V. S., and Subramanyam, B., 2008, “Analysis of Acoustic Emission Signals Using Wavelet Transformation Technique,” Def. Sci. J., 58(4), pp. 559–564.
Tang, Y-W., Tai, C-C., Su, C-C., Chen, C-Y., and Chen, J-F., 2010, “A Correlated Empirical Mode Decomposition Method for Partial Discharge Signal Denoising,” Meas. Sci. Technol., 21, p. 085106. [CrossRef]
Rosa, J. J. G., Piotrkowski, R., and Ruzzante, J. E., 2007, “Wavelet Power, Entropy and Bispectrum Applied to AE Signals for Damage Identification and Evaluation of Corroded Galvanized Steel,” IEEE Trans. Instrum. Meas., 56(6), pp. 2312–2321. [CrossRef]
He, Y., Yin, X., and Chu, F., 2008, “Modal Analysis of Rubbing Acoustic Emission for Rotor-Bearing System Based on Reassigned Wavelet Scalogram,” Trans. ASME, J. Vib. Acoust., 130, p. 061009. [CrossRef]
Surgeon, M., and Wevers, M., 1999, “Modal Analysis of Acoustic Emission Signals from CFRP Laminates,” NDT&E Int., 32, pp. 311–322. [CrossRef]
Rolo-Naranjo, A., and Montesino-Otero, M. E., 2005, “A Method for the Correlation Dimension Estimation for On-Line Condition Monitoring of Large Rotating Machinery,” Mech. Syst. Signal Process., 19(5), pp. 939–954. [CrossRef]
Castanier, M. P., and Pierre, C., 1997, “Predicting Localization via Lyapunov Exponent Statistics,” J. Sound Vib., 203(1), pp. 151–157. [CrossRef]
Pincus, S. M., 1991, “Approximate Entropy as a Measure of System Complexity,” Proc. Natl. Acad. Sci. U.S.A., 88(6), pp. 2297–2301. [CrossRef]
Smith, L. A., 1998, “Intrinsic Limits on Dimension Calculations,” Phys. Lett. A, 133(6), pp. 283–288. [CrossRef]
Pincus, S. M., 2001, “Assessing Serial Irregularity and its Implications for Health,” Ann. N.Y. Acad. Sci., 954, pp. 245–267. [CrossRef]
Abasolo, D., Hornero, R., Espinob, P., Poza, J., Sanchez, C. I., and Rosa, R. D. L., 2005, “Analysis of Regularity in the EEG Background Activity of Alzheimer's Disease Patients With Approximate Entropy,” Clin. Neurophysiol., 116, pp. 1826–1834. [CrossRef]
Ahmad, S. A., and Chappell, P. H., 2008, “Moving Approximate Entropy Applied to Surface Electromyographic Signals,” Biomed. Signal Process. Control, 3, pp. 88–93. [CrossRef]
Yan, R., and Gao, R. X., 2007, “Approximate Entropy as a Diagnostic Tool for Machine Health Monitoring,” Mech. Syst. Signal Process., 21, pp. 824–839. [CrossRef]
Fu, L., He, Z. Y., Mai, R. K., and Qian, Q. Q., 2008, “Application of Approximate Entropy to Fault Signal Analysis in Electric Power System,” Proceedings of the Chinese Society of Electric Engineering, 28(28), pp. 68–73.
Xu, Y. G., Li, L. J., and He, Z. J., 2002, “Approximate Entropy and its Applications in Mechanical Fault Diagnosis,” Chin. J. Inf. Control, 31(6), pp. 547–551.
Lin, L., and Chu, F., 2011, “Approximate Entropy as Acoustic Emission Feature Parametric Data for Crack Detection,” Nondestr. Test. Eval., 26(2), pp. 119–128. [CrossRef]
Mitrakovic, D., Grabec, I., and Sedmak, S., 1985, “Simulation of AE Signals and Signal Analysis Systems,” Ultrasonics, 9, pp. 227–232. [CrossRef]

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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