Ji Zhenxing, Jiang Peihua, Yi Haiyang, Zhuo Zhuang, Li Chunyuan, Wu Zhide
School of Mine Safety, North China Institute of Science and Technology, Langfang 065201, China.
School of Architecture Engineering, North China Institute of Science and Technology, Langfang 065201, China.
Entropy (Basel). 2022 May 25;24(6):750. doi: 10.3390/e24060750.
The issue of monitoring and early warning of rock instability has received increasing critical attention in the study of rock engineering. To investigate the damage evolution process of granite under triaxial compression tests, acoustic emission (AE) tests were performed simultaneously. This study firstly introduced two novel parameters, i.e., the coefficient of variation (CoV) of the information entropy and correlation dimension of the amplitude data from the AE tests, to identify the precursor of the failure of granite. Then the relationship between the changes in these parameters and the stress-time curve was compared and analyzed. The results of this study show that: (1) There is a strong correlation between the CoV of the information entropy and the failure process of granite. The granite failed when the CoV curve raised to a plateau, which could be used as an indicator of rock instability. (2) The fluctuation of the correlation dimension indicates the different stages during the loading process, i.e., the initial compaction stage, the linear elastic stage, the yield stage, and the failure stage. Each stage contains a descending and a rising process in the correlation dimension curve, and the exhibited starting point or the bottom point at the correlation dimension curve could be selected as the indicator point for the rock instability. (3) The combined analysis of the Information entropy and Correlation dimension can improve the accuracy of rock instability prediction. This study provides new insights into the prediction of rock instability, which has theoretical implications for the stability of subsurface engineering rock masses.
在岩石工程研究中，岩石失稳的监测与预警问题受到了越来越多的关键关注。为了研究花岗岩在三轴压缩试验下的损伤演化过程，同时进行了声发射（AE）试验。本研究首先引入了两个新参数，即声发射试验振幅数据的信息熵变异系数（CoV）和关联维数，以识别花岗岩破坏的前兆。然后对比分析了这些参数的变化与应力 - 时间曲线之间的关系。研究结果表明：（1）信息熵变异系数与花岗岩的破坏过程之间存在很强的相关性。当CoV曲线上升到平稳阶段时，花岗岩发生破坏，这可作为岩石失稳的一个指标。（2）关联维数的波动表明了加载过程中的不同阶段，即初始压实阶段、线弹性阶段、屈服阶段和破坏阶段。每个阶段在关联维数曲线中都包含一个下降和一个上升过程，关联维数曲线中出现的起始点或最低点可被选为岩石失稳的指示点。（3）信息熵和关联维数的联合分析可以提高岩石失稳预测的准确性。本研究为岩石失稳预测提供了新的见解，对地下工程岩体的稳定性具有理论意义。
