Monitoring, Warning, and Control of Rockburst in Deep Metal Mines

This paper reviews the recent achievements made by our team in the mitigation of rockburst risk. It includes the development of neural network modeling on rockburst risk assessment for deep gold mines in South Africa, an intelligent microseismicity monitoring system and sensors, an understanding of the rockburst evolution process using laboratory and in situ tests and monitoring, the establishment of a quantitative warning method for the location and intensities of different types of rockburst, and the development of measures for the dynamic control of rockburst. The mitigation of rockburst at the Hongtoushan copper mine is presented as an illustrative example. (C) 2017 THE AUTHORS. Published by Elsevier LTD on behalf of the Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license.