Featured Application: The work presented in this paper outlines three methods to analyze individual acoustic emission waves emitted within a cyclically-loaded metallic structure. Upon further development, one potential application of the proposed analysis methods would be to aid in estimating the remaining useful life of aircraft structures.Abstract: Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Several tension-tension fatigue experiments were performed with dogbone samples of aluminum 7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is measured based on visible crack growth, this work investigated fatigue damage both prior to and after crack initiation through the use of instantaneous elastic modulus degradation. Results show that one of the three entropy measurement methods appears to better assess the damage than the traditional AE features, whereas the other two entropies have unique trends that can differentiate between small and large cracks.
A parametric approach to estimating the acoustic entropy detected over the course of fatigue damage is presented. Information entropy and relative entropy is estimated through a parametric approach where trial probability density functions (PDFs) are fitted to each individual received acoustic signal as the material degrades over the cycles of loading. The PDF that produces the maximum cumulative entropy is selected to model the signals. This selection criterion is due to the fact that the PDF with higher cumulative entropy results in less bias during the selection process. The evolution trends of both information entropy and relative entropy show the stages of fatigue damage observed in the fatigue indicators such as change in hardness. The acoustic entropy has an advantage over the conventional indices of damage as it can be employed directly in the online sensor based structural health monitoring schemes as a diagnosis feature.
This paper presents the entropic damage indicators for metallic material fatigue processes obtained from three associated energy dissipation sources. Since its inception, reliability engineering has employed statistical and probabilistic models to assess the reliability and integrity of components and systems. To supplement the traditional techniques, an empirically-based approach, called physics of failure (PoF), has recently become popular. The prerequisite for a PoF analysis is an understanding of the mechanics of the failure process. Entropy, the measure of disorder and uncertainty, introduced from the second law of thermodynamics, has emerged as a fundamental and promising metric to characterize all mechanistic degradation phenomena and their interactions. Entropy has already been used as a fundamental and scale-independent metric to predict damage and failure. In this paper, three entropic-based metrics are examined and demonstrated for application to fatigue damage. We collected experimental data on energy dissipations associated with fatigue damage, in the forms of mechanical, thermal, and acoustic emission (AE) energies, and estimated and correlated the corresponding entropy generations with the observed fatigue damages in metallic materials. Three entropic theorems—thermodynamics, information, and statistical mechanics—support approaches used to estimate the entropic-based fatigue damage. Classical thermodynamic entropy provided a reasonably constant level of entropic endurance to fatigue failure. Jeffreys divergence in statistical mechanics and AE information entropy also correlated well with fatigue damage. Finally, an extension of the relationship between thermodynamic entropy and Jeffreys divergence from molecular-scale to macro-scale applications in fatigue failure resulted in an empirically-based pseudo-Boltzmann constant equivalent to the Boltzmann constant.
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