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针对单独使用声波或回弹检测法预测岩石强度的局限性问题,基于声波和回弹检测法各自的优点,采用声波—回弹综合法对岩体进行检测来反映岩体内部的裂隙特征及岩石表层硬度,并根据岩石试验数据,对比分析了基于回归分析方法和BP神经网络的岩石强度预测结果。结果表明,超声—回弹综合法对岩石强度预测精度较高,超声和回弹检测值能准确地反映岩石的强度特征。
Aiming at the limitation of predicting rock strength by using acoustic wave or rebound detection method alone, based on the respective advantages of acoustic wave and rebound detection method, the rock mass is detected by acoustic-elastic combined method to reflect the fracture characteristics of rock mass and rock Based on the rock test data, the rock strength prediction results based on regression analysis and BP neural network are comparatively analyzed. The results show that the accuracy of rock strength prediction by ultrasonic-springback method is high, and the ultrasonic and rebound values can accurately reflect the rock strength characteristics.