Affiliation:
1. Shandong University of Science and Technology
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.
Publisher
Trans Tech Publications, Ltd.
Reference5 articles.
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.
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.
3. E. Oruklu, J. Saniie: Ultrasonic Flaw Detection Using Discrete Wavelet Transform for NDE Applications, IEEE Ultrasonic Symposium, Vol. 2(2004), pp.1054-1057.
4. Z. Xiaoping, M.D. Desai: Adaptive Denoising Based on SURE Risk, IEEE Signal Processing Letters, Vol. 5, No. 10(1998), pp.265-267.
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.