Progress in study of rockburst experiments and control countermeasures

He, Mingke; Jia, Xiaohui; Gong, W.L.; Liu, Guilin; Zhang, J.T.

doi:10.1201/b11646-225

Cited by 2 publications

(1 citation statement)

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“…MS [5][6][7], EMR [8][9][10][11], and AE [12][13][14][15] monitoring technologies have been recognized by experts and scholars at home and abroad, and are widely used to monitor the early warning signals of ground pressure and other dynamic disasters. Based on the high-precision microseismic monitoring systems, Wang et al continuously monitored the coalmines in China, comprehensively analyzed the microseismic signals, and established a rockburst prediction model, which provided the basis for early risk warning in the mining process [16].…”

Section: Introductionmentioning

confidence: 99%

Multi-Index Geophysical Monitoring and Early Warning for Rockburst in Coalmine: A Case Study

Liu

Zhang

Wang

et al. 2022

IJERPH

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Rockburst is a major disaster in deep mining, restricting the safety and the production efficiency of the Laohutai Coal Mine in Fushun, Liaoning Province. To predict and prevent coalmine rockbursts, a comprehensive method based on multi-instrument monitoring is proposed by using a YDD16 acoustic-electromagnetic monitor and microseismic monitoring system, including microseismic (MS) monitoring, electromagnetic radiation (EMR) monitoring, and acoustic emission (AE) monitoring. Field investigation shows that MS, AE, and EMR signals have abnormal precursors before rockbursts in a new working face. Based on the fluctuation theory and D-S evidence theory, the multi-index geophysical monitoring and early warning technology for rockburst disasters in the Laohutai Coal Mine are established. The method has been applied to the prediction of rockbursts in the Laohutai Coal Mine. The application shows that the acoustic-electromagnetic synchronous monitoring and early warning technology can accurately identify the potential rockburst risk and trigger an early warning, which is more reliable than a single method. The case study of the Laohutai rockburst shows that the joint early warning method of multi-instrument comprehensive monitoring can predict the possibility of rockbursts.

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