Abstract
This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. There are two main approaches that are considered: (i) long-range correlation analysis using both the Hurst (H) and the detrended fluctuation analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data that were collected from two application examples: a glass fiber-reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis was also performed to reference the study of the other methods. The results indicate that the proposed methods yield reliable indication of failure in the studied structures.
Highlights
Damage processes in heterogeneous material remains an open research problem.Classical theoretical methods rely on treating the material as a continuum, where macro parameters are regularized to facilitate the application of differential analysis, such as using homogenization [1,2,3] or plasticity-inspired damage theories [4,5,6]
We investigate the behavior of long-range correlations of the temporal series that are studied using rescaled range (R/S*) analysis [22] and detrended fluctuation analysis (DFA) [23]
Notice that the purpose of the present work is to present the parameters that are related to DFA, R/S*, and natural time domain (NT) analyses, which could be used in a concomitant way with other strategies of analysis that are used nowadays
Summary
Classical theoretical methods rely on treating the material as a continuum, where macro parameters are regularized to facilitate the application of differential analysis, such as using homogenization [1,2,3] or plasticity-inspired damage theories [4,5,6]. This approach contradicts experimental evidence, which shows that the process is spasmodic and has evident discontinuity patterns. For an excellent revision regarding these approaches, refer to Jenabidehkordi, 2019 [9]
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