Time-frequency manifold as a signature for machine health diagnosis

IEEE Transactions on Instrumentation and Measurement

Volumn 61, Issue 5, 2012, Pages 1218-1230

  He, Qingbo ^a   Liu, Yongbin ^a   Long, Qian ^a   Wang, Jun ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Machine health diagnosis; manifold learning; phase space reconstruction (PSR); time frequency distribution (TFD); time frequency manifold (TFM)

Indexed keywords

MACHINE HEALTH; MANIFOLD LEARNING; PHASE SPACE RECONSTRUCTION; TIME FREQUENCY; TIME-FREQUENCY DISTRIBUTIONS;

FLOW FIELDS; PHASE SPACE METHODS; ROBUSTNESS (CONTROL SYSTEMS);

CONDITION MONITORING;

EID: 84862825547     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2012.2183402     Document Type: Conference Paper

References (25)

1. Z. K. Peng and F. L. Chu, "Application of the wavelet transform in machine condition monitoring and fault diagnostics: A review with bibliography," Mech. Syst. Signal Process., vol. 18, no. 2, pp. 199-221, Mar. 2004.
2. J. K. Hammond and P. R. White, "The analysis of non-stationary signals using time-frequency methods," J. Sound Vib., vol. 190, no. 3, pp. 419-447, 1996.
3. R. Yan and R. X. Gao, "Hilbert-Huang transform-based vibration signal analysis for machine health monitoring," IEEE Trans. Instrum. Meas., vol. 55, no. 6, pp. 2320-2329, Dec. 2006.
4. G. Gelle, M. Colas, and C. Serviere, "Blind source separation: A new preprocessing tool for rotating machines monitoring?" IEEE Trans. Instrum. Meas., vol. 52, no. 3, pp. 790-795, Jun. 2003
5. A. Malhi and R. X. Gao, "PCA-based feature selection scheme for machine defect classification," IEEE Trans. Instrum. Meas., vol. 53, no. 6, pp. 1517-1525, Dec. 2004.
6. J. D. Jiang, J. Chen, and L. S. Qu, "The application of correlation dimension in gearbox condition monitoring," J. Sound Vib., vol. 223, no. 4, pp. 529-541, Jun. 1999.
7. Z. Feng, M. J. Zuo, and F. Chu, "Application of regularization dimension to gear damage assessment," Mech. Syst. Signal Process., vol. 24, no. 4, pp. 1081-1098, May 2010.
8. R. Yan and R. X. Gao, "Complexity as a measure for machine health evaluation," IEEE Trans. Instrum. Meas., vol. 53, no. 4, pp. 1327-1334, Aug. 2004.
9. G. F. Wang, Y. B. Li, and Z. G. Luo, "Fault classification of rolling bearing based on reconstructed phase space and Gaussian mixture model," J. Sound Vib., vol. 323, no. 3-5, pp. 1077-1089, Jun. 2009.
10. Q. He, F. Kong, and R. Yan, "Subspace-based gearbox condition monitoring by kernel principal component analysis," Mech. Syst. Signal Process., vol. 21, no. 4, pp. 1755-1772, May 2007.
11. C.Wang and R. X. Gao, "Wavelet transform with spectral post-processing for enhanced feature extraction," IEEE Trans. Instrum. Meas., vol. 52, no. 4, pp. 1296-1301, Aug. 2003.
12. A.-O. Boudraa and J.-C. Cexus, "EMD-based signal filtering," IEEE Trans. Instrum. Meas., vol. 56, no. 6, pp. 2196-2202, Dec. 2007.
13. Q. He, Z. Feng, and F. Kong, "Detection of signal transients using independent component analysis and its application in gearbox condition monitoring," Mech. Syst. Signal Process., vol. 21, no. 5, pp. 2056-2071, Jul. 2007.
14. J. Yang, J. Xu, D. Yang, andM. Li, "Noise reduction method for nonlinear time series based on principal manifold learning and its application to fault diagnosis," Chin. J. Mech. Eng., vol. 42, pp. 154-158, 2006.
15. S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 290, no. 5500, pp. 2323-2326, Dec. 2000.
16. J. B. Tenenbaum, V. Silva, and J. C. Langford, "A global geometric framework for nonlinear dimensionality reduction," Science, vol. 290, no. 5500, pp. 2319-2323, Dec. 2000.
17. Z. Zhang and H. Zha, "Principal manifolds and nonlinear dimensionality reduction via tangent space alignment," SIAM J. Sci. Comput., vol. 26, no. 1, pp. 313-338, 2005.
18. M. Li, J. Xu, J. Yang, D. Yang, and D.Wang, "Multiple manifolds analysis and its application to fault diagnosis," Mech. Syst. Signal Process., vol. 23, no. 8, pp. 2500-2509, Nov. 2009.
19. Q. Jiang, M. Jia, J. Hu, and F. Xu, "Machinery fault diagnosis using supervised manifold learning," Mech. Syst. Signal Process., vol. 23, no. 7, pp. 2301-2311, Oct. 2009.
20. I. Lopez and N. Sarigul-Klijn, "Distance similarity matrix using ensemble of dimensional data reduction techniques: Vibration and aerocoustic case studies," Mech. Syst. Signal Process., vol. 23, no. 7, pp. 2287-2300, Oct. 2009.
21. Q. He, Y. Liu, J.Wang, J.Wang, and C. Gong, "Time-frequency manifold for gear fault signature analysis," in Proc. IEEE Int. Instrum. Meas. Technol. Conf., Hangzhou, China, May 10-12, 2011, pp. 491-495.
22. M. Kennel, R. Brown, and H. Abarbanel, "Determining embedding dimension for phase-space reconstruction using a geometrical construction," Phys. Rev. A, Atomic Mol. Opt. Phys., vol. 45, no. 6, pp. 3403-3411, Mar. 1992.
23. L. Cao, "Practical method for determining the minimum embedding dimension of a scalar time series," J. Phys. D, vol. 110, no. 1/2, pp. 43-50, Dec. 1997.
24. F. Takens, "Detecting strange attractors in turbulence," in Dynamical System and Turbulence, D. A. Rand and L.-S. Young, Eds. Berlin, Germany: Springer-Verlag, 1981, pp. 366-387.
25. X. S. Lou and K. A. Loparo, "Bearing fault diagnosis based on wavelet transform and fuzzy inference," Mech. Syst. Signal Process., vol. 18, no. 5, pp. 1077-1095, Sep. 2004.