Denoising and Defect Diagnosis of Material Ultrasonic Detection signal Based on Best Wavelet Packet Base

Xiao Ling Yan; Shi Yun Dong; Wang Long Wang; Bin Shi Xu

doi:10.4028/www.scientific.net/AMM.239-240.52

Paper Titles

Acoustic Modal Test and Finite Element Analysis on Vehicle Cavity
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Design and Implementation of Ultrasonic Ranging System
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Identify on Acoustic Emission Signals of Tank Bottom Corrosion Using Hidden Markov Model
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Application of Parametric Acoustic Receiving Array to Underwater Acoustic Measurement
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Denoising and Defect Diagnosis of Material Ultrasonic Detection signal Based on Best Wavelet Packet Base
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The Realization for Sound Pressure Unit Using Laser Doppler Anemometry in a Travelling Wave Tube
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Optimal Selection of Long Time Acoustic Features Using GA for the Assessment of Vocal Fold Disorders
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The Study of Using Ultrasonic Sensors to Detect Degradation Characteristics of the Ferrite Core
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Attenuation Characteristics of Sound Wave in Silicon Dioxide ER Fluid
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 239-240Denoising and Defect Diagnosis of Material...

Denoising and Defect Diagnosis of Material Ultrasonic Detection signal Based on Best Wavelet Packet Base

Abstract:

The use of ultrasonic nondestructive testing of material internal defect，ultrasonic signal acquired at actual working spot usually includes large amount of noise.Extraction of the defect characteristic information will be influeced greatly if the ultrasonic signal is not effectively denoised. A new method based on best wavelet packet base is present to denoise and detect the ultrasonic signal. The superiority of new method is verified by simulation examples. Experiment of processing ultrasonic signal which comes from the 45 Steel specimen with flaws has been implemented. The accurate information that characterizes of defect size,location can be extracted from the processing result, the results show that the new method based on best wavelet packet base is in favor of enhancing the degree of accuracy for quantitatively analyzing the defect inside the material.