Abstract
The noise suppression techniques with wavelet transform (WT) are widely used in nondestructive testing and evaluation (NDT&E), especially in ultrasonics. But the wavelet based filter has the property of equal Q-factor, so, it is impossible to choose the central frequency and the bandwidth arbitrarily at the same time. This paper develops a new technique using WT to eliminate this drawback. In this paper, a weak ultrasonic signals identification method by using the optimal parameter Gabor wavelet transform is proposed. We address the choice of the optimal central frequency and bandwidth of the Gabor wavelet using the kurtosis maximization algorithm. The central frequency and bandwidth of the optimal parameter Gabor wavelet matched that of the ultrasonic signal very well. Numerical and experimental results have been presented to evaluate the effectiveness of the optimal parameter Gabor wavelet transform on ultrasonic flaw detection. This technique is a simpler and effective technique for processing heavy noised ultrasonic signals.
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References
Shou-Peng Song and Pei-Wen Que, Wavelet Based Noise Suppression Technique and Its Application to Ultrasonic Flaw Detection, Ultrasonics, 2006, vol. 44, pp. 188–193.
Honarvar Farhang, Sheikhzadeh Hamid, et al., Improving the Time Resolution and Signal-to-Noise Ratio of Ultrasonic NDT Signals, Ultrasonics, 2004, vol. 41, pp. 755–763.
Abbate, A., Koay, J., et al., Application of Wavelet Transform Signal Processor to Ultra-Sound, IEEE-Ultrasonics Symposium, 1994, pp. 1147–1152.
Abbate, A., Koay, J., et al., Signal Detection and Noise Suppression Using a Wavelet Transform Signal Processor: Application to Ultrasonic Flaw Detection, IEEE TUFF, 1997, vol. 44, no. 1, pp. 14–26.
Zhang Guang-Ming, Hou Ceng-Gang, et al., Optimal Frequency-to-Band Ratio of Wavelet in Ultrasonic on-Destructive Evaluation, Ultrasonics, 2001, vol. 39, pp. 13–17.
Liang Wei and Que Pei-Wen, Maximum Nongaussianity Parameters Estimation of Ultrasonic Echoes and Its Application in Ultrasonic Non-Destructive Evaluation, Meas. Sci. Technol., 2007, vol. 18, pp. 3743–3750.
Zhang Guang-Ming, Hou Ceng-Gang, et al., Optimal Frequency-to-Band Ratio of Wavelet in Ultrasonic Nondestructive Evaluation, Ultrasonics, 2001, vol. 39, pp. 13–17.
Abbate, A., Koay, J., et al., Signal Detection and Noise Suppression Using a Wavelet Transform Signal Processor: Application to Ultrasonic Flaw Detection, IEEE TUFF, 1997, vol. 44, no. 1, pp. 14–26.
Chen, Jian-Feng and Zagebski, J.A., Non-Gaussian Versus Non-Rayleigh Statistical Properties of Ultrasound Echo Signals, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 1988, vol. 41, no. 4, pp. 438–440.
D’Hooge Bernard, O. and JanFriboulet, D., Statistics of the Radio-Frequency Signal Based on K Distribution with Application to Echocardiography, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2006, vol. 53, no. 9, pp. 1689–1694.
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Original Russian Text © Han Yong, Chen Guo-Guang, 2009, published in Defektoskopiya, 2009, Vol. 45, No. 6, pp. 90–97.
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Han, Y., Chen, GG. Maximum kurtosis principle for the parameter selection of Gabor wavelet and its application to ultrasonic signal processing. Russ J Nondestruct Test 45, 436–442 (2009). https://doi.org/10.1134/S1061830909060084
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DOI: https://doi.org/10.1134/S1061830909060084