Application of Acoustic Emission (AE) in mining and earth sciences: a review
Keywords:Acoustic Emission; Signal processing techniques; Earth sciences and Mining engineering; SMART evaluations
One of the most important products of the majority of tools, processes and, phenomena in mining engineering and earth sciences are high-frequency elastic waves, often referred to as acoustic waves. These acoustic waves can be a useful tool for prediction and measurement, monitoring and diagnosis. Due to the importance of engineering activities that should be specific, measurable, available, reliable and time-based (SMART), Acoustic Emission (AE) techniques can be inte- grated into engineering operations such as excavation to give exact estimations or simplify some aspects of investiga- tions. Hence, these techniques are expected to play an increasing role in the detection, monitoring, and measurement in engineering applications. With the development of acoustic signal processing methods in earth sciences and the grow- ing need for accurate, fast, and cost-effective prediction, monitoring and measurement methods, AE tools and tech- niques are expected to turn into powerful alternatives to current methods. The purpose of this paper is to review the application of the acoustic methods as a tool in various projects. For this purpose, the application of AE methods has been reviewed in different fields related to earth sciences including mining engineering, drilling engineering, geology, petroleum engineering, and other related fields. According to the purpose of using these methods, the application of AE is divided into three groups: prediction and estimation, monitoring and performance assessment, and detection. The use of AE methods, among other laboratory or in-situ methods, is very fast and accurate, and by only installing specific sen- sors with data logging equipment, it has been able to process and analyse data online and remotely. Finally, the possibil- ity of using AE techniques in design and calculating in various projects and as a tool for decision making was evaluated.
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