Abstract:

In order to effectively prevent coal and gas outburst accidents in coal mines, a combined weighting grey clustering risk assessment model for coal and gas outburst is proposed. Firstly, based on trajectory crossover theory, prediction indicators are selected from three aspects: coal seam physical properties, gas indicators, and coal seam occurrence conditions, and a risk assessment index system is constructed. Then, the Improved Analytic Hierarchy Process (IAHP) and Entropy Weight Method (EWM) are used to determine the weights of each indicator, and a grey fuzzy evaluation standardized level judgment matrix for each indicator is constructed based on the grey clustering principle. The coal and gas outburst level is predicted based on the principle of maximum membership degree. Finally, taking the 12407 fully mechanized top coal caving face of Ulan Mulun Coal Mine as an application example, the effectiveness of the combination weighting grey clustering evaluation model was verified. The results show that the danger level of coal and gas outburst in this working face is Ⅴ. The model calculation results are basically consistent with the actual situation on site. The physical properties of coal seams are the main inducing factors. The evaluation results are consistent with the actual situation. It is proved that the model is scientific and effective.

Key words: coal and gas outburst, combination weighting, grey clustering, hazard assessment, outstanding level