Abstract
Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.
Similar content being viewed by others
References
Bartelt, H. O., Brenner, K. H. and Lohmann, A. W., 1980, “The Wigner Distribution Function and its Optical Production,”Optics Communications, Vol. 32, pp. 32–38.
Bo-Suk Yang, Tian Han and Won-Woo Hwang, 2005, “Fault Diagnosis of Rotating Machinery Based on Multi-Class Support Vector Machines,”Journal of Mechanical Science and Technology (KSME I.J.), Vol. 19, pp. 846–859.
Chang Woo Lee, Hyun Kyoo Kang and Kee Hyun Shin, 2004, “A Study on the Fault Diagnosis of the 3-D Roll Shape in Cold Rolling,”KSME International journal, Vol. 18, pp. 2174–2181.
Cohen, L., 1995, Time-Frequency Analysis, Prentice-Hall, Englewood Cliffs, NJ.
Dalpiaz, G., Rivola, A. and Rubini, R., 2000, “Effectiveness and Sensitivity of Vibration Processing Techniques for Local Fault Detection in Gears,”Mechanical Systems and Signal Processing, Vol. 14, pp. 387–412.
Datig, M. and Schlurmann, T., 2004, “Performance and Limitations of the Hilbert-Huang Transformation (HHT) with an Application to Irregular Water Waves,”Ocean Engineering, Vol. 31, pp. 1783–1834.
Dong Hoon Kim, Sun Ho Kim and Jun-Yeob Song, 2005a, “Diagnosing the Cause of Operational Faults in Machine Tools with an Open Architecture CNC,”Journal of Mechanical Science and Technology (KSME I.J.), Vol. 19, pp. 1597–1610.
Dong-Hoon Kim, Sun-Ho Kim and Kwang-Sik Koh, 2005b, “CNC-Implemented Fault Diagnosis and Web-Based Remote Services.”Journal of Mechanicl Science and Technology (KSME I.J.), Vol. 19, pp. 1095–1100.
Hlawatsch, F. and Kozek, W., 1993, “The Wigner Distribution of a Linear Signal Space,”IEEE Transaction on Signal Processing, Vol. 41, pp. 1248–1258.
Huang, N. E., Shen, Z. and Long, S. R. et al., 1998, “The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis,”Proceeding of Royal Society London, Series A, Vol. 454, pp. 903–995.
Huang, N. E., Shen, Z. and Long, S. R., 1999, “A New View of Nonlinear Water Waves: The Hilbert Spectrum,”Annual Review of Fluid Mechanics, Vol. 31, pp. 417–457.
Huang, W., Shen, Z., Huang, N. E. and Fung, Y. C., 1999, “Nonlinear Indicial Response of Complex Nonstationary Oscillations as Pulmonary Hypertension Responding to Step Hypoxia,”Proc of the National Academy of Sciences, USA, Vol. 96, pp. 1834–1839.
Huang, W., Shen, Z., Huang, N. E. and Fung, Y. C., 1998a, “Engineering Analysis of Biological Variables: An Example of Blood Pressure over One Day,”Proc of the National Academy of Sciences, USA, Vol. 95, pp. 4816–4821.
Huang, W., Shen, Z., Huang, N. E. and Fung, Y. C., 1998b, “Engineering Analysis of Intrinsic Mode and Indicial Response in Biology: the Transient Response of Pulmonary Blood Pressure to Step Hypoxia and Step Recovery,”Proc. of the National Academy of Science, USA, Vol. 9, pp. 12766–12771.
Jae Hyuk Oh, Chang Gu Kim and Young Man Cho, 2004, “Diagnostics and Prognostics Based on Adaptive Time-Frequency Feature Discrimination,”KSME International Journal, Vol. 18, pp. 1537–1548.
Leuridan, J. and Auweraer, H. V. D., 1994, “The Analysis of Non-Stationary Dynamics Signals,”Sound and vibration, Vol. 11 pp. 14–26.
Lin, J. and Qu, L., 2000, “Feature Extraction Based on Morlet Wavelet and its Application for Mechanical Fault Diagnosis,”Journal of Sound and Vibration, Vol. 234, pp. 135–148.
Loutridis, S. J., 2004, “Damage Detection in Gear System using Empirical mode Decomposition,”Engineering Structure, Vol. 26, pp. 1833–1841.
Matz, G. and Hlawatsch, F., 2003, “Wigner Distribution (Nearly) Everywhere: Time-Frequency Analysis of Signals, Systems, Random Process, Signal Spaces, and Frames,”Signal Processing, Vol. 83, pp. 1355–1378.
Meng, Q. and Qu, L., 1991, Rotating Machinery Fault Diagnosis Using Wigner Distribution, Mechanical Systems and Signal Processing, Vol. 5, pp. 155–166.
Montesinos, M., Munoz-Cobo, J. and Perez, C., 2003, “Hilbert-Huang Analysis of BWR Detector Signals: Application to DR Calculation and to Corrupted Signal Analysis,”Annals of Nuclear Energy, 30, pp. 715–727.
Nunes, J., Bouaoune, Y., Delechelle, E., Niang, O. and Bunel, P., 2003, “Image Analysis by Bidimensional Empirical Mode Decomposition,”Image and Vision Computing, Vol. 21, pp. 1019–1026.
Quek, S., Tua, P. and Wang, Q., 2003 “Detecting Anomalies in Beams and Plate Based on the Hilbert-Huang Transform of Real Signals,”Smart Materials and Structures, Vol. 12, pp. 447–460.
Randall, R. B., 1982, “A New Method of Modelling Gear Faults,”Journal of Mechanical Design, Vol. 104, pp. 259–267.
Shin, Y. S. and Jeon, J. J., 1993, “Pseudo Wigner-Ville Time-Frequency Distribution and its Application to Machinery Condition Monitoring,”Shock and Vibration, Vol. 1, pp. 65–76.
Staszewski, W. J., Worden, K. and Tomlinson, G. R., 1997, The-Frequency Analysis in Gearbox Fault Detection Using the Wigner-Ville Distribution and Pattern Recognition,”Mechanical Systems and Signal Processing, Vol. 11, pp. 673–692.
Wahl, T. J. and Bolton, J. S., 1993, “The Application of the Wigner Distribution to the Identification of Structure-Borne noise Components,”Journal of Sound and Vibration, Vol. 163, pp. 101–122.
Wang, L., Koblinsky, C., Howden, S. and Huang, N. E., 1999, “Interannual Variability in the South China Sea from Expendable Bathythermograph Data,”Journal of Geophysical Research, Vol. 104, pp. 509–523.
Wang, W. J. and Mcfadden, P. D., 1995, “Application of Orthogonal Wavelet to Early Gear Damage Detection,”Mechanical Systems and Signal Processing, Vol. 9, pp. 497–507.
Wu, M. L., Schubert, S. and Huang, N. E., 1999, “The Development of the South Asian Summer Monsoon and the Intraseasonal Oscillation,”Journal of Climate, Vol. 7, pp. 2054–2075.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, H., Zhang, Y. & Zheng, H. Wear detection in gear system using Hilbert-Huang transform. J Mech Sci Technol 20, 1781–1789 (2006). https://doi.org/10.1007/BF03027572
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF03027572