Literature DB >> 25737229

Acoustic emission detection for mass fractions of materials based on wavelet packet technology.

Xianghong Wang1, Jianjun Xiang2, Hongwei Hu2, Wei Xie2, Xiongbing Li3.   

Abstract

Materials are often damaged during the process of detecting mass fractions by traditional methods. Acoustic emission (AE) technology combined with wavelet packet analysis is used to evaluate the mass fractions of microcrystalline graphite/polyvinyl alcohol (PVA) composites in this study. Attenuation characteristics of AE signals across the composites with different mass fractions are investigated. The AE signals are decomposed by wavelet packet technology to obtain the relationships between the energy and amplitude attenuation coefficients of feature wavelet packets and mass fractions as well. Furthermore, the relationship is validated by a sample. The larger proportion of microcrystalline graphite will correspond to the higher attenuation of energy and amplitude. The attenuation characteristics of feature wavelet packets with the frequency range from 125 kHz to 171.85 kHz are more suitable for the detection of mass fractions than those of the original AE signals. The error of the mass fraction of microcrystalline graphite calculated by the feature wavelet packet (1.8%) is lower than that of the original signal (3.9%). Therefore, AE detection base on wavelet packet analysis is an ideal NDT method for evaluate mass fractions of composite materials.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acoustic emission; Attenuation; Mass fraction; Non-destructive testing; Wavelet packet

Year:  2015        PMID: 25737229     DOI: 10.1016/j.ultras.2015.02.001

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  1 in total

1.  Study on Attenuation Characteristics of Acoustic Emission Signals with Different Frequencies in Wood.

Authors:  Feilong Mao; Saiyin Fang; Ming Li; Changlin Huang; Tingting Deng; Yue Zhao; Gezhou Qin
Journal:  Sensors (Basel)       Date:  2022-08-11       Impact factor: 3.847

  1 in total

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