基于BP神经网络的隧道岩爆预测模型研究

在分析岩爆主要影响因素的基础上,建立了基于BP神经网络岩爆预测模型,采用已有岩爆发生数据作为训练样本对网络进行训练,利用收敛的网络进行岩爆烈度预测,预测结果与实际吻合,说明利用人工神经网络预测岩爆发生烈度是一种可行的方法。     

Fractal analysis on the spatial distribution of acoustic emission in the failure process of rock specimens

The spatial distribution of acoustic emission (AE) events in the failure process of several rock specimens was acquired us-ing an advanced AE acquiring and analyzing system.The box counting method (BCM) was employed to calculate the fractal dimen-sion (FD) of AE spatial distribution.There is a similar correlation between the fractal dimension and the load strength for different rock specimens.The fractal dimension presents a decreasing trend with the increase of load strength.For the same kind of specimens,their FD values will decrease to the level below a relatively same value when they reach failure.This value can be regarded as the critical value,which implies that the specimen will reach failure soon.The results reflect that it is possible to correlate the damage of rock with a macroscopic parameter,the FD value of AE signals.Furthermore,the FD value can be also used to forecast the final fail-ure of rock.This conclusion allows identifying or predicting the damage in rock with a great advantage over the classic theory and is very crucial for forecasting rockburst or other dynamic disasters in mines.