4.6 Article

Damage Analysis of Composite CFRP Tubes Using Acoustic Emission Monitoring and Pattern Recognition Approach

Journal

MATERIALS
Volume 14, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/ma14040786

Keywords

acoustic emission; CFRP composite tube; unsupervised learning approach; failure mechanism

Funding

  1. Innovative and additive manufacturing technology-new technological solutions for 3D printing of metals and composite materials [CZ.02.1.01/0.0/0.0/17_049/0008407]
  2. Czech Science Foundation (GACR) project [19-03282S]

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The acoustic emission method was used to monitor the damage mechanisms in carbon-fiber-reinforced polymer composite tubes during the three-point bending test. A two-step technique was applied to analyze the data, leading to the identification of failure mechanisms such as matrix cracking, fiber break, decohesion, and debonding. This study also includes a comprehensive parametric acoustic emission signal analysis of the individual clusters, as well as comparisons with existing research papers.
The acoustic emission method has been adopted for detection of damage mechanisms in carbon-fiber-reinforced polymer composite tubes during the three-point bending test. The damage evolution process of the individual samples has been monitored using the acoustic emission method, which is one of the non-destructive methods. The obtained data were then subjected to a two-step technique, which combines the unsupervised pattern recognition approach utilizing the short-time frequency spectra with the boundary curve enabling the already clustered data to be additionally filtered. The boundary curve identification has been carried out on the basis of preliminary tensile tests of the carbon fiber sheafs, where, by overlapping the force versus time dependency by the acoustic emission activity versus time dependency, it was possible to identify the boundary which will separate the signals originating from the fiber break from unwanted secondary sources. The application of the presented two-step method resulted in the identification of the failure mechanisms such as matrix cracking, fiber break, decohesion, and debonding. Besides the comparison of the results with already published research papers, the study presents the comprehensive parametric acoustic emission signal analysis of the individual clusters.

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