【摘要】 为有效进行隧道围岩超前优化分级,提出基于属性数学理论和隧道地震波勘探系统的围岩超前优化分级方法。选取隧道地震波勘探系统可有效识别的物理力学参数作为属性评价指标,并结合围岩工程地质分类和RMR系统分类方法,确定围岩等级与各评价指标之间的对应关系;通过构建单指标属性测度函数,计算得到单指标属性测度及样本综合属性测度;应用置信度准则对隧道样本的围岩等级进行属性识别,从而建立围岩优化分级的属性识别模型。在工程实例分析研究中,评价结果与模糊综合评价法以及GA-SVM法的评价结果具有较好的一致性,从而验证属性识别模型评价结果的合理性及可靠性。更多还原

【Abstract】 In order to realize surrounding rock optimized classification effectively,an attribute recognition model based on attribute mathematics theory and tunnel seismic prediction system was put forward.Firstly,physical and mechanical parameters which could be identified effectively by tunnel seismic prediction system were selected as attribute evaluation index,and the corresponding relationship between surrounding rock grades and evaluation index was determined combined with engineering geological classification and RMR system.Secondly,attribute measurement functions were constructed to compute attribute measurement of single index and synthetic attribute measurement.Lastly,the identification and classification of surrounding rock grades of tunnel samples were recognized by the confidence criterion,then attribute recognition model was established for surrounding rock optimized classification.The exemplification study shows that the synthetic assessment results agree well with the results obtained by fuzzy comprehensive evaluation and GA-SVM,and the rationality and reliability of the result obtained through attribute recognition model is verified.更多还原