Abstract
Accurate prediction of coal and gas outburst risk is essential for outburst prevention and control. In this paper, the evolution law of electromagnetic radiation (EMR) and acoustic emission (AE) in the process of deformation and rupture of coal and rock are analyzed. Then, the characteristic laws of EMR and AE signals in coal roadway during the driving process of Jiulishan Coal Mine are studied. The critical values of acoustic and electromagnetic monitoring and warning is solved using the fuzzy pattern recognition method. Results show that: (1) The change trending of AE and EMR signals is consistent with stress level. However, there are abrupt changes in the acoustic and electromagnetic signals before the stress peak. The degree of signal fluctuation is significant. (2) EMR is mainly produced by rheological and frictional deformation after coal body ruptures, while AE is mainly caused by the rupture of coal and rock. The intensity and pulse of EMR can better respond and early-warn the danger of coal and gas outburst during tunneling. (3) By using fuzzy pattern recognition method, the critical values of acoustic and electromagnetic monitoring and warning can be solved. It is more reliable to predict the outburst danger when the membership degree \( \mu_{A} (x_{0} ) \) is 0.6–0.8.
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