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Abstract Rockburst is a complicated dynamic instability phenomenon during the rock excavation of deep rock masses in high in-situ stress zone. It is affected by many factors，and the roles of various factors in the formation process of rockburst are not yet clear. Then，the complex relationship between rockburst and its influencing factors is considered as a grey system，which can be studied by the grey clustering method. According to the causes of rockburst and its characteristics，the main factors of rockburst，which are the maximum tangential stress of the cavern wall ，uniaxial compressive strength ，uniaxial tensile strength and the elastic energy index of rock ，are chosen in the analysis. Moreover，the evaluation indexes including the stress coefficient of rock / ，the brittleness coefficient of rock / ，and the elastic energy index of rock are used to establish the modified grey evaluation model for rockburst prediction through the optimization of grey whitenization weight function. Compared with the traditional grey evaluation model，the modified model doesn?t have the crossing properties of grey cluster and meets the normality well，which is more reasonable in theory. Based on the rockburst data of some deep rock projects at home and abroad，the modified model is adopted to predict the possibility and classification of rockburst. Compared with the traditional model，the prediction error of the modified model is smaller. In addition，the prediction results of the modified model are close to the practical records，which proves that the model is effective and available. Therefore，the proposed method provides a practical way to accurately predict the possibility and classification of rockburst in deep underground engineering.
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Received: 03 June 2013
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2013, Vol. 32 
