Study on Wavelet Denoise and Characteristic Extraction of Echo Signal to Flaw Classification in Ultrasonic Testing
LIU Xu
XIA Jin-dong
Wu Miao
Abstract：There are usually two problems in flaw classification in ultrasonic testing. One is the noise in echo signal in ultrasonic testing, which is sometimes very difficult to eliminate. The other is the criterion problem for validity evaluation in echo signal characteristic extraction. A noise eliminating method for ultrasonic signal with wavelet denoise was presented and sort separability criterion was used to solve the second problem in this paper. And these two methods were verified by some experiments. Firstly wavelet transform was used in denoising process of ultrasonic signal; Then sort separability criterion was used to evaluate the characteristic choice of flaw signals; And finally the characteristic values of flaws in demodulated signal were classified by RBF neural network to validate the above methods. Results of the experiments show that due to making the best use of the information of time and frequency domain at the same time in ultrasonic echo signals, wavelet deniose algorithm not only decreases the noises obviously, but also locates flaws accuratelly. And the sort separability criterion can also play the role of being a quantification measure on the characteristic extracting of flaw signals.
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Publication Date：2001-05-02
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 248-251 )