The Identification of the Deformation Stage of a Metal Specimen Based on Acoustic Emission Data AnalysisReport as inadecuate


The Identification of the Deformation Stage of a Metal Specimen Based on Acoustic Emission Data Analysis


The Identification of the Deformation Stage of a Metal Specimen Based on Acoustic Emission Data Analysis - Download this document for free, or read online. Document in PDF available to download.

1

College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China

2

Beijing Key Lab of Membrane Science and Technology, College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, China





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Authors to whom correspondence should be addressed.



Academic Editor: Vittorio M. N. Passaro

Abstract The acoustic emission AE signals of metal materials have been widely used to identify the deformation stage of a pressure vessel. In this work, Q235 steel samples with different propagation distances and geometrical structures are stretched to get the corresponding acoustic emission signals. Then the obtained acoustic emission signals are de-noised by empirical mode decomposition EMD, and then decomposed into two different frequency ranges, i.e., one mainly corresponding to metal deformation and the other mainly corresponding to friction signals. The ratio of signal energy between two frequency ranges is defined as a new acoustic emission characteristic parameter. Differences can be observed at different deformation stages in both magnitude and data distribution range. Compared with other acoustic emission parameters, the proposed parameter is valid in different setups of the propagation medium and the coupled stiffness. View Full-Text

Keywords: acoustic emission; metal deformation degree; tensile test; signal energy ratio; empirical mode decomposition acoustic emission; metal deformation degree; tensile test; signal energy ratio; empirical mode decomposition





Author: Shenao Zou 1, Fengying Yan 2, Guoan Yang 1,* and Wei Sun 2,*

Source: http://mdpi.com/



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