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Quality evaluation of metal surfaces treatment by wavelet analysis
Author(s) -
L. Deineha,
А. Berezhnoi,
В. Н. Козлов,
Vladislav Sudakov
Publication year - 2021
Publication title -
novì materìali ì tehnologìï v metalurgìï ta mašinobuduvannì
Language(s) - English
Resource type - Journals
eISSN - 2786-7358
pISSN - 1607-6885
DOI - 10.15588/1607-6885-2021-2-10
Subject(s) - wavelet , discrete wavelet transform , daubechies wavelet , stationary wavelet transform , second generation wavelet transform , wavelet packet decomposition , orthogonal wavelet , lifting scheme , wavelet transform , mathematics , artificial intelligence , pattern recognition (psychology) , computer science , algorithm
Purpose. Analyze the effectiveness of using wavelet analysis to assess the quality of metal surfaces. Investigate the possibility of using wavelet analysis in ultrasonic flaw detection. Determine the optimal wavelet families and their criteria for assessing the quality of metal surface processing. Research methods. Orthogonal wavelets are considered: Daubechies wavelet, Simlet wavelet and Coiflet wavelet, which provide the possibility of performing a discrete wavelet transform procedure. The criteria influencing the effectiveness of ultrasonic signal filtering by methods using wavelet analysis are considered. Ultrasonic signals were filtered using wavelet functions. Results. It has been determined that for successful signal filtering, the selected wavelet method must provide a discrete wavelet transformation and have a similarity in the wavelet function shape in the local features of the ultrasonic signals flaw detector. During the work, a rigid threshold for limiting the detail coefficients of wavelet analysis was chosen, as it is the best for filtering tasks. The filtering efficiency is confirmed by the relatively high signal to noise ratio, as well as by the fact that the shape of the pulse extracted from the defect remained almost unchanged. Scientific novelty.  When using the Daubechies and Coiflet wavelets as basic functions, as a result of wavelet filtering, it was possible to increase the signal to noise ratio by 20 dB and confidently isolate the useful signal against the background noise, which indicates the prospects of using this kind of transformations in filtering problems. Practical value. The obtained solutions can be used for implementation in signal filtering algorithms in digital processing units of automated non-destructive ultrasonic control systems.

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