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江胜华, 周智, 欧进萍. 基于磁场梯度定位的边坡变形监测原理[J]. 岩土工程学报, 2012, 34(10): 1944-1949.
引用本文: 江胜华, 周智, 欧进萍. 基于磁场梯度定位的边坡变形监测原理[J]. 岩土工程学报, 2012, 34(10): 1944-1949.
JIANG Sheng-hua, ZHOU Zhi, OU Jin-ping. Slope deformation monitoring principle based on magnetic gradient tensor[J]. Chinese Journal of Geotechnical Engineering, 2012, 34(10): 1944-1949.
Citation: JIANG Sheng-hua, ZHOU Zhi, OU Jin-ping. Slope deformation monitoring principle based on magnetic gradient tensor[J]. Chinese Journal of Geotechnical Engineering, 2012, 34(10): 1944-1949.

基于磁场梯度定位的边坡变形监测原理

Slope deformation monitoring principle based on magnetic gradient tensor

  • 摘要: 现有边坡变形传感器易受雨水、泥石流、滚石等环境的影响,且在深部变形监测时,存在仪器布设较繁琐的问题。基于磁测的原理,采用磁性标签制作智能石头,通过磁力梯度仪和智能石头建立边坡变形监测系统。采用Levenberg-Marquardt算法(LM算法)改进遗传算法,实现基于磁场梯度的磁性目标(智能石头)定位,避免磁性目标的磁感应强度与地球磁场分离的问题,同时解决了一般优化算法的收敛性。此算例中,基于磁场梯度定位的边坡位移监测精度达到0.01m,在实际的边坡监测中,其精度可通过增大智能石头的磁矩、改变磁力梯度仪的位置进行调整。

     

    Abstract: The existing slope deformation sensors are easily influenced by rainwater, mud-rock flows, rolling stones and other environmental factors, and the arrangement of equipment is not convenient for the internal deformation monitoring. Based on the magnetic detection, the smart rock is fabricated with magnetic label, and a slope monitoring system is established with the combination of smart rock and magnetometer. The genetic algorithm is improved by the Levenberg-Marquardt algorithm to realize the localization of smart rock using magnetic gradient tensors. The separation of earth's magnetic field and the smart rock’s magnetic strength is avoided through localization based on the magnetic gradient tensors, and the convergence and the accuracy of optimization are solved during the magnetic inversion. In the example, the slope deformation monitoring by magnetic inversion can reach the accuracy of 0.01 m through the magnetic gradient tensors, but the accuracy can be adjusted by increasing the moment of magnetic label and by changing the location of magnetic gradiometer in the practical engineering monitoring.

     

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