4.2 Article

Combined early warning method for rockburst in a Deep Island, fully mechanized caving face

Journal

ARABIAN JOURNAL OF GEOSCIENCES
Volume 9, Issue 20, Pages -

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s12517-016-2776-0

Keywords

Deep coal mine; Rockburst; Island coal face; Microseismic monitoring; Electromagnetic emission; Drilling cutting method; Combined early warning method

Funding

  1. National Basic Research Program of China [2014CB046905]
  2. National Natural Science Foundation of China [51274191, 51374140]
  3. Doctoral Fund of Ministry of Education of China [20130095110018]

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Rockbursts annually cause hundreds of casualties and huge economic losses in China. The possibility of rockbursts occurring in a deep island, fully mechanized caving coal face is much higher than in a normal face. To predict and prevent rockbursts in this type of coal face, a comprehensive approach based on multi-instrument monitoring, including microseismic (MS) monitoring, electromagnetic emission (EME) monitoring, and the drilling cutting method (DCM), has been proposed. The case of working face 1304 in the Yangcheng coal mine in Shandong Province, China, was analyzed to test the combined early warning method. In situ investigations showed many early warning precursors before a rockburst, such as a period of silence in MS activity, persistent rising of EME intensity values and pulse numbers, and a large jolt of EME. Based on the quantitative early warning indexes, the combined early warning method for rockbursts in coal face 1304 was established, which mainly includes three rockburst risk judgment conditions and one rockburst risk identification condition. This method has been applied to rockburst forecasting in the Yangcheng coal mine. The application showed that this comprehensive approach could accurately identify potential rockburst risks and trigger early warnings. The case study demonstrated that the likelihood of a rockburst occurring can be forecasted by the combined early warning method based on multi-instrument monitoring.

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