Experimental study of coal burst risk prediction using fractal dimension analysis of AE spatial distribution
RIS ID
142826
Abstract
© 2020 Elsevier B.V. The sustainable and clean mining of coal is essential for Australia and the world as coal is a key energy source. However, with the increase of mining depth, many coalmines are facing potential coal burst hazards as deep mining always associated with high gravitational stress and complicated geology. More recently, the coal burst risk is highlighted by accidents happened at Austar and Appin coalmines in Australia. Assumedly due to long time mining history with relatively shallow mining depth, coalmines in Australia has no coal burst history and corresponding risk controlling plans, technics and equipment. This paper proposes a novel method for coal burst risk prediction based on fractal dimension analysis of AE spatial distribution. Besides, this paper introduces the mathematical analysis method of fractal dimension based on dimension calculation formula and MATLAB coding. Finally, obvious fractal dimension decrease of AE spatial distribution is observed in experimental study of coal samples with high burst propensity, which promises the feasibility of coal bursts prediction through AE monitoring.
Publication Details
Yang, X., Ren, T. & He, X. (2020). Experimental study of coal burst risk prediction using fractal dimension analysis of AE spatial distribution. Journal of Applied Geophysics, 177