A rock burst often occurs during the construction period of deep-buried underground caverns. How to predict and prevent it is an urgent problem in underground engineering, especially in large hydropower stations. Combining grey correlation method, principal component analysis (PCA) and cloud theory, a novel analysis method that is proposed to evaluate rock burst. First, seven indices, namely, R_c, R_c/σ₁, R_c/σ_t, σ_θ/R_c, W_et, H and K_V, are selected. Considering the relationship between these indices, the grey correlation method is used to analyze these indices and reduce them. According to the correlation coefficients, the five indices, namely, R_c/σ₁, R_c/σ_t, σ_θ/R_c, W_et and K_V, consist of the final evaluated system. Second, the weight of each index is calculated using principal component analysis (PCA). Take into consideration of the ambiguity and randomness of rock burst; the multi-dimensional cloud model is used to evaluate the rock burst level. The proposed model is applied to a case study of the Jiangbian hydropower station to certify the feasibility and effectiveness of the novel method. The results are basically consistent with the actual rock burst level. At last, the selection of the evaluation system and the accuracy of the multi-dimensional cloud model are discussed. This novel method provides a new idea for the risk assessment of rock burst in deep-buried underground caverns.

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深埋地下洞室岩爆风险评估：一种新的分析方法

在深埋地下洞室施工期间经常发生岩爆。如何预测和预防它是地下工程特别是大型水电站中的紧迫问题。结合灰色关联法，主成分分析法和云理论，提出了一种新的岩爆评价方法。第一，七个指数，即，- [R _Ç，- [R _Ç /σ ₁，- [R _ç /σ_吨，σ _θ / R _Ç，w ^_等，ħ和ķ _V选择。考虑到这些指标之间的关系，采用灰色关联法对这些指标进行分析和归约。根据相关系数，五个指标，即，- [R _Ç /σ ₁，- [R _ç /σ_吨，σ _θ / R _Ç，w ^_等和ķ _V，由最终评估系统组成。其次，使用主成分分析（PCA）计算每个指数的权重。考虑到岩爆的模糊性和随机性；多维云模型用于评估岩爆水平。将该模型应用于江边水电站的案例研究，验证了该方法的可行性和有效性。结果与实际的岩爆水平基本一致。最后讨论了评估系统的选择和多维云模型的准确性。该新方法为深埋地下洞室岩爆风险评估提供了新思路。