Use of composite higher order spectra for faults diagnosis of rotating machines with different foundation flexibilities

Measurement: Journal of the International Measurement Confederation

Volumn 70, Issue , 2015, Pages 47-61

  Yunusa Kaltungo, Akilu ^a   Sinha, Jyoti K ^a   Nembhard, Adrian D ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Composite bispectrum; Composite trispectrum; Data fusion; Faults diagnosis; Flexible foundation; Rotating machines

Indexed keywords

DATA FUSION; FOUNDATIONS; LOCATION; ROTATING MACHINERY;

BISPECTRUM; FAULTS DIAGNOSIS; FLEXIBLE FOUNDATIONS; ROTATING MACHINE; TRISPECTRUM;

FAULT DETECTION;

EID: 84927154803     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2015.03.041     Document Type: Article

References (36)

1. C.B.N.S. Balla, J.K. Sinha, and A.R. Rao Importance of proper installation for satisfactory operation of rotating machines Adv. Vibr. Eng. 4 2 2005 137 142
2. G. Gazetas Analysis of machine foundation vibrations: state of the art Soil Dyn. Earthquake Eng. 2 1 1983 2 42
3. J.K. Sinha, W. Hahn, K. Elbhbah, G. Tasker, I. Ullah, Vibration investigation for low pressure turbine last stage blade failure in steam turbines of a power plant, in: Proceedings of ASME Turbo Expo 2012 (GT2012), June 11-15, 2012, Copenhagen, Denmark.
4. Y. Ishida Cracked rotors: industrial machine case histories and nonlinear effects shown by simple Jeffcott rotor Mech. Syst. Signal Process. 22 4 2008 805 817
5. N. Bachschmid, P. Pennacchi, and A. Vania Identification of multiple faults in rotor systems J. Sound Vib. 254 2 2002 327 366
6. A.W. Lees, J.K. Sinha, and M.I. Friswell Model-based identification of rotating machines Mech. Syst. Signal Process. 23 6 2009 1884 1893
7. P. Pennacchi, N. Bachschmid, and A. Vania A model-based identification method of transverse cracks in rotating shafts suitable for industrial machines Mech. Syst. Signal Process. 20 2006 2112 2147
8. A.S. Sekhar Crack identification in a rotor system: a model-based approach J. Sound Vib. 270 2004 887 902
9. J.K. Sinha, A.W. Lees, and M.I. Friswell Estimating unbalance and misalignment of a flexible rotating machine from a single run-down J. Sound Vib. 272 2004 967 989
10. P. Pennacchi, N. Bachschmid, A. Vania, G.A. Zanetta, and L. Gregori Use of modal representation for the supporting structure in model-based fault identification of large rotating machinery: part 1 - theoretical remarks Mech. Syst. Signal Process. 20 2006 662 681
11. A.S. Sekhar Model-based identification of two cracks in a rotor system Mech. Syst. Signal Process. 18 2004 977 983
12. A.K.S. Jardine, D. Lin, and D. Banjevic A review on machinery diagnostics and prognostics implementing condition-based maintenance Mech. Syst. Signal Process. 20 2006 1483 1510
13. J. Lee, J. Ni, D. Djurdjanovic, H. Qiu, and H. Liao Intelligent prognostics tools and e-maintenance Comput. Ind. 57 2006 476 489
14. Z.K. Peng, Z.Q. Lang, and S.A. Billings Crack detection using nonlinear output frequency response functions J. Sound Vib. 301 2007 777 788
15. Z. Peng, Y. He, Q. Lu, and F. Chu Feature extraction of the rub-impact rotor system by means of wavelet analysis J. Sound Vib. 259 4 2003 1000 1010
16. I.M. Howard Higher-order spectral techniques for machine vibration condition monitoring Proc. Instit. Mech. Eng., Part G: J. Aero-space Eng. 211 4 1997 211 219
17. M.A. Hassan, A.E. Bayoumi, and Y.J. Shin Quadratic-nonlinearity index based on bicoherence and its application in condition monitoring of drive-train components IEEE Trans. Instrum. Meas. 63 3 2014 719 728
18. B. Jang, C. Shin, E.J. Powers, W.M. Grady, Machine fault detection using bicoherence spectra, in: Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference, vol. 3, Como, Italy, May 18-20, 2004, pp. 1661-1666.
19. L. Bouillaut, and M. Sidahmed Cyclostationary approach and bilinear approach: comparison, applications to early diagnosis for helicopter gearbox and classification method based on HOCs Mech. Syst. Signal Process. 15 5 2001 923 943
20. C.J. Li, J. Ma, and B. Hwang Bearing condition monitoring by pattern recognition based on bicoherence analysis of vibration Proc. Instit. Mech. Eng., Part C 210 C3 1996 277 285
21. A. Rivola, P.R. White, Use of higher order spectra in condition monitoring: simulation and experiments, in: Proceedings of DETC99: 1999 ASME Design Engineering Technical Conferences, September 12-15, 1999, Las Vegas, Nevada.
22. Y. Li, X. Wang, J. Lin, and S. Shi A wavelet bicoherence-based quadratic nonlinearity feature for translational axis condition monitoring Sensors 14 2 2014 2071 2088
23. Y. Li, J. Lin, X. Wang, and Y. Lei Biphase randomization wavelet bicoherence for mechanical fault diagnosis Measurement 49 2014 407 420
24. J.K. Sinha Higher order spectra for crack and misalignment identification in shaft of a rotating machine Struct. Health Monit. 6 4 2007 325 334
25. A. Yunusa-Kaltungo, J.K. Sinha, K. Elbhbah, HOS analysis of measured vibration data on rotating machines with different simulated faults, in: Advances in Condition Monitoring of Machinery in Non-Stationary Operations, Chapter 6 (Proceedings of the International Conference on Condition Monitoring of Machinery in Non-Stationary Operations 2013). Springer Publishing, Series: 11236, ISBN: 978-3-642-39347-1.
26. A. Yunusa-Kaltungo, and J.K. Sinha Combined bispectrum and trispectrum for faults diagnosis in rotating machines Proc. Instit. Mech. Eng., Part O: J. Risk Reliab. 228 4 2014 419 428
27. A. Yunusa-Kaltungo, Vibration based condition monitoring of rotating machines, A second year PhD progression report submitted to the School of Mechanical, Aerospace and Civil Engineering, University of Manchester, 2014.
28. K. Elbhbah, and J.K. Sinha Vibration-based condition monitoring of rotating machines using a composite spectrum J. Sound Vib. 332 11 2013 2831 2845
29. J.K. Sinha, and K. Elbhbah A future possibility of vibration-based condition monitoring of rotating machines Mech. Syst. Signal Process. 34 1-2 2013 231 240
30. B.C.B.N. Suryam, K.K. Meher, J.K. Sinha, and A.R. Rao Coherence measurement for early contact detection between two components J. Sound Vib. 290 1-2 2006 519 523
31. A.C. McCormick, and A.K. Nandi Bispectral and trispectral features for machine condition diagnosis IEEE Proc. - Vision, Image Signal Process. 146 5 1999 229 234
32. Z. Li, X. Yan, C. Yuan, J. Zhao, and Z. Peng Fault detection and diagnosis of a gearbox in marine propulsion systems using bispectrum analysis and artificial neural networks J. Mar. Sci. Appl. 10 2011 17 24
33. J.W.A. Fackrell, P.R. White, J.K. Hammond, R.J. Pinnington, and A.T. Parsons The interpretation of the bispectra of vibration signals-1: Theory Mech. Syst. Signal Process. 9 3 1995 257 266
34. J.W.A. Fackrell, P.R. White, J.K. Hammond, R.J. Pinnington, and A.T. Parsons The interpretation of the bispectra of vibration signals-II: Experimental results and applications Mech. Syst. Signal Process. 9 3 1995 267 274
35. W.B. Collis, P.R. White, and J.K. Hammond Higher-order spectra: the bispectrum and trispectrum Mech. Syst. Signal Process. 12 3 1998 375 394
36. J.K. Sinha Vibration Analysis Instruments and Signal Processing 2015 CRC Press ISBN - 13: 978-1-4822-3144-1