Abstract
As a non-destructive testing technology with fast response and high resolution, acoustic emission is widely used in material monitoring. The material deforms under stress and releases elastic waves. The wave signals are received by piezoelectric sensors and converted into electrical signals for rapid storage and analysis. Although the acoustic emission signal is not the original stress signal inside the material, the typical statistical distributions of acoustic emission energy and waiting time between signals are not affected by signal conversion. In this review, we first introduce acoustic emission technology and its main parameters. Then, the relationship between the exponents of power law distributed AE signals and material failure state is reviewed. The change of distribution exponent reflects the transition of the material’s internal failure from a random and uncorrelated state to an interrelated state, and this change can act as an early warning of material failure. The failure process of materials is often not a single mechanism, and the interaction of multiple mechanisms can be reflected in the probability density distribution of the AE energy. A large number of examples, including acoustic emission analysis of biocemented geological materials, hydroxyapatite (human teeth), sandstone creep, granite, and sugar lumps are introduced. Finally, some supplementary discussions are made on the applicability of Båth’s law.
Highlights
Geotectonic processes are often perceived as slow, encapsulated in the colloquial expression of ‘long geological time scales’
Compared with the traditional mechanical constitutive model and failure criterion, statistical physics provides an alternative research framework for disaster research [46,47,48]. They are based on elastic responses, as measured by seismic waves in the geological context, while acoustic emission (AE) spectroscopy is used on an engineering and laboratory time and length scale
By analyzing the probability density distribution of Acoustic emission (AE) energy in each subinterval, the critical exponent decreases with the increase in superjerk ranks, which can be used as a warning signal of impeding disasters (Figure 5)
Summary
Geotectonic processes are often perceived as slow, encapsulated in the colloquial expression of ‘long geological time scales’. With improved experimental facilities to identify the details of geological time dependences, we understand that they occur on many different time scales. Even those which evolve over thousands of years, such as some metamorphic processes, proceed by short-time atomistic changes which add up to the observed long-term evolution. Long-term time evolution is often constituted by a long sequence of short singular events and research has partly shifted from the continuous description of geological processes to the analysis of these singular events from spontaneous changes in chemical composition, atomic ordering, phase transitions, and crack propagation to earthquakes, the collapse of structures in the mining industry and so forth.
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