Rock burst prediction based on coefficient of variation and sequence analysis-multidimensional normal cloud model

The prediction of rock burst intensity grade is influenced by the comprehensive action of various indexes,and the accurate prediction and evaluation of rock burst grade is an urgent problem to be solved in rock mechanics research. A rock burst prediction method based on coefficient of variation and sequence correlation analysis-multi-dimensional normal cloud model is proposed. In this method,the elastic deformation energy index Wet,stress coefficient σθ/σc,brittleness coefficient σc/σt and rock uniaxial compressive strength σc are used as rock burst grade evaluation factors. Aiming at the problem that the accuracy of comprehensive weight determination of rock burst index is not high,the comprehensive weights are obtained based on the coefficient of variation and sequence analysis method. Combined with the multi-dimensional forward cloud generator,the membership degree of different rock burst grade is calculated,and then the sample rock burst prediction levels are given. The research shows that the graded prediction results of rock burst intensity grades based on the coefficient of variation and sequential analysis method-multidimensional normal cloud model are in good agreement with the actual situation,which shows that the method is feasible and can provide a new research method for rock burst grade prediction.