Time-Frequency Feature Extraction of a Cracked Shaft Using an Adaptive Kernel

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Adaptive time-frequency representations have many advantages compared with conventional methods. In this paper, a new method is proposed to adapt Smoothed Pseudo Wigner- Ville distribution to match signal’s time-frequency content. It is based on maximizing a local timefrequency concentration measure for different time and frequency smoothing window lengths. Subsequently, the optimized values are used for constructing an adaptive kernel over time. The proposed transform is then applied to vibration signals of healthy and cracked shafts which are acquired through run-up, and the crack signature is obtained. Results show that enhanced improvement in resolution is obtained while the computational cost is not very high.

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Edited by:

Patrick Sean Keogh

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37-44

Citation:

M. Behzad and A.R. Ghias, "Time-Frequency Feature Extraction of a Cracked Shaft Using an Adaptive Kernel ", Applied Mechanics and Materials, Vols. 5-6, pp. 37-44, 2006

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October 2006

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$38.00

[1] D.F. Shi, F. Tsung and P.J. Unsworth: Adaptive time-frequency decomposition for transient vibration monitoring of rotating machinery, Mechanical Systems and Signal Processing, 2004, pp.127-141.

DOI: https://doi.org/10.1016/s0888-3270(03)00085-2

[2] D.L. Jones and T.W. Parks: A high resolution data-adaptive time-frequency representation, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 38, No. 12, Dec. (1990).

DOI: https://doi.org/10.1109/29.61539

[3] R.G. Baraniuk and D.L. Jones: A signal-dependent time-frequency representation: Optimal kernel design, IEEE Transactions on Signal Processing, Vol. 41, No. 4, April 1993, p.15891602.

DOI: https://doi.org/10.1109/78.212733

[4] D.L. Jones and R.G. Baraniuk: A simple scheme for adapting time-frequency representations, IEEE Transactions on Signal Processing, Vol. 42, No. 12, Dec. (1994).

DOI: https://doi.org/10.1109/78.340790

[5] Shie Qian and Dapang Chen: Joint time-frequency analysis, Prentice Hall, (1996).

[6] R.G. Baraniuk and D.L. Jones: A signal-dependent time-frequency representation: Fast Algorithm for Optimal kernel design, IEEE Transactions on Signal Processing, Vol. 42, No. 1, Jan. 1994, pp.134-146.

DOI: https://doi.org/10.1109/78.258128

[7] R.G. Baraniuk and D.L. Jones: A radial Gaussian signal-dependent time-frequency representation, IEEE International Conference on Acoustics, Speech, and Signal Processing, Toronto, 1991, pp.3181-3184.

DOI: https://doi.org/10.1109/icassp.1991.150131

[8] Mark J. Coates, Christophe Molina and William J. Fitzgerald: Regionally optimized kernels for time-frequency distributions, IEEE, (1998).

[9] R.G. Baraniuk and D.L. Jones: A signal-dependent time-frequency representation: Optimal kernel design, IEEE Transactions on Signal Processing, Vol. 41, No. 4, April 1993, p.15891602.

DOI: https://doi.org/10.1109/78.212733

[10] G. Illescas R: Vibration analysis for characterizing cracked shafts behaviour in operation, MSc Thesis, SEPI-ESIME, Instituto Politecnio Nacional (in Spanish, 2001).

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