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突水灾害已成为危及隧道安全施工的重大问题,为了实现隧道突水灾变演化过程的监测和灾害预警,将电阻率层析成像法尝试引入到隧道突水的监测工作中,提出了一种基于图像灰度相关性理论的电阻率层析成像监测信息定量评价方法。首先,针对非地质缺陷类和地质缺陷类这两种典型的突水类型进行概化,得到了突水灾变演化过程不同阶段的地电模型,为隧道突水实时监测数值模拟奠定了基础。其次,采用有限单元法进行电阻率层析成像法突水实时监测数值模拟,揭示了电阻率图像对突水灾变演化过程的响应特征,通过对突水灾变演化过程电阻率图像灰度相关性的定量分析,发现相关性系数小于0.5(或0.3)的样本点数目大幅增多,且相关性分布和正演图像标准差急剧增大,是突水发生的重要前兆特征。最后,进行了隧道突水电阻率层析成像法实时监测模型试验,较准确地捕捉到了突水前兆信息,实现了突水灾害预警,表明电阻率层析成像法用于突水实时监测是可行的。
The water inrush disaster has become a major problem that endangers the construction of the tunnel. In order to monitor the evolution of the water inrush disaster and early warning of the disaster, the resistivity tomography method is introduced to monitor the water inrush of the tunnel. Quantitative evaluation method of resistivity tomography monitoring information of image gray correlation theory. First of all, according to the generalization of two typical types of water inrush, such as non-geological defects and geological defects, the geoelectric model at different stages of the process of water inrush disaster catastrophe is established, which lays the foundation for the numerical simulation of water inrush monitoring in real time. Secondly, the finite element method is used to conduct the numerical simulation of water inrush monitoring by resistivity tomography. The response characteristics of the resistivity image to the water flooding catastrophe evolution process are revealed. Through the gray correlation of resistivity images during the process of water flooding catastrophic evolution Quantitative analysis showed that the number of sample points with correlation coefficient of less than 0.5 (or 0.3) increased significantly, and the correlation distribution and standard deviation of forward images increased sharply, which was an important precursor of water inrush. Finally, a real-time monitoring model test of water inrush resistivity tomography was carried out to capture the water inrush precursors accurately and realize the early warning of water inrush. It is feasible to use the resistivity tomography in real-time water inrush monitoring of.