Planetary gearbox fault diagnostic method using acoustic emission sensors

IET Science, Measurement and Technology

Volumn 9, Issue 8, 2015, Pages 936-944

  Yoon, Jae ^a   He, David ^a  

^a University of Illinois at Chicago   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC EMISSION TESTING; DATA ACQUISITION; EPICYCLIC GEARS; FAILURE ANALYSIS; HETERODYNING; LEARNING ALGORITHMS; VIBRATION ANALYSIS;

ACOUSTIC EMISSION SENSORS; CONDITION INDICATORS; DATA ACQUISITION SYSTEM; EMPIRICAL MODE DECOMPOSITION; FAULT DIAGNOSIS METHOD; FAULT DIAGNOSTIC METHODS; HETERODYNE TECHNIQUE; SAMPLING FREQUENCIES;

FAULT DETECTION;

EID: 84948689440     PISSN: 17518822     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-smt.2014.0375     Document Type: Article

References (37)

1. Sheng S.: 'Gearbox reliability database: yesterday, today, and tomorrow'. NREL Technical Report, No. PR-5000-63106, 2014, pp. 1-14
2. Sheng S. Link H. LaCava W.: 'Wind turbine drivetrain condition monitoring during GRC phase 1 and phase 2 testing'. NREL Technical Report NREL/TP, 5000-52748, 2011, pp. 1-49
3. Astridge D.G.: 'Helicopter transmissions - design for safety and reliability'. J. Aerosp. Eng., 1989, 203, (2), pp. 123-138
4. Samuel P.D. Conroy J.K. Pines D.J.: 'Planetary transmission diagnostics'. NASA Technical Report: NASA/CR, 2004-213068, 2004, pp. 1-83
5. McFadden P.D.: 'A technique for calculating the time domain averages of the vibration of the individual planet gears and the sun gear in an epicyclic gearbox', J. Sound Vib., 1991, 144, (1), pp. 163-172
6. McFadden P.D.: 'Window functions for the calculation of the time domain averages of the vibration of the individual planet gears and sun gear in an epicyclic gearbox', J. Vib. Acoust., 1994, 116, (2), pp. 179-187
7. Lewicki D.G. Laberge K.E. Ehinger R.T.: 'Planetary gearbox fault detection using vibration separation technique'. NASA Technical Report: NASA/CR, 2004-213068, 2011, pp. 1-14
8. Yoshioka T. Fujiwara T.: 'Application of acoustic emission technique to detection of rolling bearing failure', Annu. Meeting ASME, 1984, 14, (1), pp. 55-76
9. Tandon N. Mata S.: 'Detection of defects in gears by acoustic emission measurements', J. Acoust. Emission, 1999, 17, (1-2), pp. 23-27
10. Tandon N. Nakra B.C.: 'Comparison of vibration and acoustic measurement techniques for the condition monitoring of rolling element bearings', Tribol. Int., 1992, 25, (3), pp. 205-212
11. Scheer C. Reimche W. Bach F.W.: 'Early fault detection at gear units by acoustic emission and wavelet analysis', J. Acoust. Emission, 2007, 25, (1), pp. 331-340
12. Qu Y. He D. Bechhoefer E.: 'A new acoustic emission sensor based gear fault detection approach', Int. J. PHM, 2013, 4, (Special Issue on Wind Turbine PHM), pp. 1-14
13. Qu Y. He D. Yoon J.: 'Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors - a comparative study'. Sensors, 2014, 14, (1), pp. 1372-1393
14. Bechhoefer E. Qu Y. Zhu J.: 'Signal processing technique to improve an acoustic emission sensors', Proc. Annual Conf. PHM Society, New Orleans, LA, USA, October 2013, pp. 1-8
15. Yoon J. He D. Van Hecke B.: 'A PHM approach to additive manufacturing equipment health monitoring, fault diagnosis, and quality control', Annual Conf. PHM Society, Fort Worth, TX, USA, Sep. 2014, pp. 1-9
16. Van Hecke B. He D. Qu Y.: 'On the use of spectral averaging of acoustic emission signals for bearing fault diagnostics', J. Vib. Acoust., 2014, 136, (6), pp. 1-13
17. Huang N. Shen Z. Long S.: 'The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis', Proc. R. Soc. Lond. A, 1971, 454, pp. 903-995
18. Yu D. Cheng J. Yang Y.: 'Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings', Mech. Syst. Signal Process., 2005, 19, (2), pp. 259-270
19. Yan R. Gao R.: 'Hilbert-Huang transform-based vibration signal analysis for machine health monitoring', IEEE Trans. Instrum. Meas., 2006, 55, (6), pp. 2320-2329
20. Yan R. Gao R.X.: 'Rotary machine health diagnosis based on empirical mode decomposition', J. Vib. Acoust., 2008, 130, (2), pp. 1-12
21. Liu B. Riemenschneider S. Xu Y.: 'Gearbox fault diagnosis using empirical mode decomposition and Hilbert spectrum', Mech. Syst. Signal Process., 2006, 20, (3), pp. 718-734
22. He D. Li R. Zhu J.: 'Plastic bearing fault diagnosis based on a two-step data mining approach', IEEE Trans. Ind. Electron., 2013, 60, (8), pp. 3429-2013
23. Van M. Kang H. Shin K.: 'Rolling element bearing fault diagnosis based on non-local means de-noising and empirical mode decomposition', IET Sci. Meas. Technol., 2014, 8, (6), pp. 571-578
24. Amarnath M. Praveen Krishna I.R.: 'Empirical mode decomposition of acoustic signals for diagnosis of faults in gears and rolling element bearings', IET Sci. Meas. Technol., 2012, 6, (4), pp. 279-287
25. He D. Li R. Zhu J.: 'Data mining based full ceramic bearing fault diagnostic system using AE sensors', IEEE Trans. Neural Netw., 2011, 22, (12), pp. 2022-2031
26. Yoon J. He D. Qiu B.: 'Full ceramic bearing fault diagnosis using LAMSTAR neural network', IEEE PHM Conf., Gaithersburg, MD, USA, June 2013, pp. 1-9
27. Fessenden R. A.: 'Electric Signaling Apparatus'. US Patent 1050441A, 14 January
28. Qu Y. Van Hecke B. He D.: 'Gearbox fault diagnosis using AE sensors with low sampling rate', J. Acoust. Emission, 2013, 31, (1), pp. 67-90
29. Teager H.M. Teager S.M.: 'Evidence for nonlinear sound production mechanisms in the vocal tract', in Hardcastle W. J. Marchal A. (ed.): 'Time frequency and time-scale analysis' (Springer, Netherlands, 1992, vol. 55), pp. 345-348
30. Altman N.S.: 'An introduction to kernel and nearest-neighbor nonparametric regression', Am. Stat., 1992, 46, (3), pp. 175-185
31. Rumelhart D.E. Hinton G.E. Williams R.J.: 'Learning representations by back-propagating errors', Nature, 1986, 323, (6088), pp. 533-536
32. Graupe D. Kordylewski H.: 'A large memory storage and retrieval neural network for adaptive retrieval and diagnosis', Int. J. Softw. Eng. Knowl. Eng., 1998, 8, (1), pp. 115-138
33. Kohonen T.: 'Self-organization and associative memory', (Springer-Verlag, Berlin, 1984)
34. Kordylewski H. Graupe D. Liu K.: 'A novel large-memory neural network as an aid in medical diagnosis applications', IEEE Trans. Inf. Technol. B, 2001, 5, (3), pp. 202-209
35. Graupe D.: 'Principles of artificial neural networks' (World Scientific Publishing, 3rd edn., 2013)
36. Bartelmus W. Zimroz R.: 'Vibration spectra characteristic frequencies for condition monitoring of mining machinery compound and complex gearboxes', Sci. P. Inst. Min. Conf., 2011, 133, (40), pp. 17-34
37. Yoon J. He D. Van Hecke B.: 'Vibration based wind turbine planetary gearbox fault diagnosis using spectral averaging', AWEA Wind Power Conf., Orlando, FL, USA, May 2015