Deep mining has changed the original stress state of surrounding rock, and the stress in surrounding rock has been redistributed and self-stabilized, resulting in different degrees of stress concentration. Therefore, rock burst and other dynamic disasters are very easy to occur, which poses a serious threat to mine safety production. Since the occurrence of rock burst is affected and controlled by many factors, its intensity is random and ambiguous. In this paper, elastic energy index Wet, rock fragility index Is, rock fragility coefficient Ku, in-situ stress index S, energy dissipation index k and tangential stress criterion are selected as master control factor sets from the aspects of lithology and stress respectively. The degree of rock burst intensity is classified and used as evaluation set. Membership function of each index is obtained by using the method of reducing semi-trapezoidal distribution method, and the fuzzy relation matrix is constructed. The weight of each index is determined by analytic hierarchy process, then the fuzzy comprehensive evaluation model of rock burst intensity is established. Finally, the evaluation model is used to evaluate the stability of surrounding rock when the mining depth is 480m, 495m and 510m in Beiminghe iron mine. It is verified that the comprehensive evaluation model of rock burst prediction can improve the reliability of prediction results. This study has theoretical guiding significance for the prediction and prevention of rock burst in mines.

1. Introduction

The elastic deformation energy stored in rock mass is affected by the redistribution of stress during excavation, and will be released violently in an instant. At this time, rock will burst and ejection will occur. At the same time, there are some characteristics of rock cracking, spalling, ejection, throwing and loud noise, which are rock burst phenomena (Gong et al. 2019, Zhou et al.2019). In the construction of deep rock mass such as hard rock mine, deep-buried tunnel and underground water power station, rock burst is likely to occur. It is a geological hazard with great harmfulness, which is sudden and difficult to effectively prevent and predict. After the occurrence of rock burst, it poses a threat to the life of the constructors and causes severe damage to the progress of the project. Heavy impact, causing great losses to people's property (Khademian et al. 2019, Fan et al. 2019). Therefore, it is of great significance and far-reaching development prospects to study the mechanism and process of rock burst. Rock burst is a worldwide problem, which has a varying degree of impact on many countries around the world. At present, many scholars at home and abroad have done a lot of research work on the mechanism of rock burst, prediction and evaluation, and have also achieved useful results. Researchers have put forward the catastrophe theory (Xia et al. 2015, Yang et al.2016), the fuzzy comprehensive discriminant method (Miao et al. 2017), the grey relational analysis theory (Wu et al. 2015), the artificial neural network (Chakraborty et al.2017) and other comprehensive prediction methods of non-linear mathematics.

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