Characterization of Failure Mechanism in Composite Materials Through Fractal Analysis of Acoustic Emission Signals

TL;DR

This study uses fractal analysis of acoustic emission signals to identify and differentiate failure mechanisms in composite materials during tensile and flexural testing.

Contribution

It introduces a comprehensive fractal analysis approach to characterize failure signatures in composite materials based on acoustic emission data.

Findings

Fractal indices can distinguish different failure mechanisms.

Hurst, DFA, minimal cover, and boxcounting indices are effective.

Acoustic emission signals contain identifiable signatures of failure types.

Abstract

In this paper it is presented a detailed numerical investigation of acoustic emission signals obtained from test samples of fibreglass reinforced polymeric matrix composites, when subjected to tensile and flexural tests. Various fractal indices, characteristic of the signals emitted at the different structural failures of the test samples and which satisfy non-stationary distributions, have been determined. From the results obtained for these indices, related to the Hurst analysis, detrended fluctuation analysis, minimal cover analysis and to the boxcounting dimension analysis, it has been shown they can discriminate the different failure mechanisms and, therefore, they constitute their signature.