Application of Adaptive Wavelet Thresholding to Ultrasonic Signal Compression of Aluminum Alloy Forgings

Shou Shan Liu; Chuan Jiang Wang; Li Jun Bi; Chang Zhi Lv

doi:10.4028/www.scientific.net/AMR.658.89

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Application of Adaptive Wavelet Thresholding to Ultrasonic Signal Compression of Aluminum Alloy Forgings
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 658Application of Adaptive Wavelet Thresholding to...

Application of Adaptive Wavelet Thresholding to Ultrasonic Signal Compression of Aluminum Alloy Forgings

Abstract:

In this paper, for the purpose of ultrasonic signal compression and the coherent noise depressing in nondestructive test of aluminum alloy forging, the mathematical model of defect echoes is discussed and confirmed. And then the wavelet kernel is also confirmed according the waveform of the defect echoes. As the algorithms of standard hard thresholding and soft thresholding of wavelet transform can not bring out effective compression and depression to the coherent noise, an adaptive wavelet thresholding algorithm is introduced. Experimental results indicate that the adaptive wavelet thresholding algorithm can offer effective signal compression and depression to the coherent noise.

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Periodical:

Advanced Materials Research (Volume 658)

Pages:

89-92

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.658.89

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Online since:

January 2013

Authors:

Shou Shan Liu, Chuan Jiang Wang, Li Jun Bi, Chang Zhi Lv

Keywords:

Adaptive Thresholding, Aluminum Alloy Forging, Discrete Wavelet Transform (DWT), Ultrasonic Nondestructive Test

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References

[1] G. Cardoso, J. Sanjie: Performance Evaluation of DWT, DCT, and WHT for Compression of Ultrasonic Signals, IEEE Ultrasonic Symposium, Vol. 3(2004), pp.2314-2317.

DOI: 10.1109/ultsym.2004.1418304

Google Scholar

[2] G. Cardoso, J. Sanjie: Compression of Ultrasonic Data Using Transform Thresholding and Parameters Estimation Techniques, IEEE Ultrasonics Symposium, Vol. 1(2002), pp.837-840.

DOI: 10.1109/ultsym.2002.1193527

Google Scholar

[3] E. Oruklu, J. Saniie: Ultrasonic Flaw Detection Using Discrete Wavelet Transform for NDE Applications, IEEE Ultrasonic Symposium, Vol. 2(2004), pp.1054-1057.

DOI: 10.1109/ultsym.2004.1417956

Google Scholar

[4] Z. Xiaoping, M.D. Desai: Adaptive Denoising Based on SURE Risk, IEEE Signal Processing Letters, Vol. 5, No. 10(1998), pp.265-267.

DOI: 10.1109/97.720560

Google Scholar

[5] L. Shoushan, Y. Chenlong, L. Ling: Adaptive Wavelet Thresholding Based Ultrasonic Signal Denoising, Journal of Zhejiang University (Engineering Science), Vol. 41, No. 9(2007), pp.1557-1560.

Google Scholar