XU Ha-ning, XIAO Hui, DENG Ju-zhi. Research on Prediction Algorithm of Landslide Deformation Based on SIMM-UKF and Resistivity Imaging Technology[J]. Acta Electronica Sinica, 2021, 49(2): 354-361.
DOI:
XU Ha-ning, XIAO Hui, DENG Ju-zhi. Research on Prediction Algorithm of Landslide Deformation Based on SIMM-UKF and Resistivity Imaging Technology[J]. Acta Electronica Sinica, 2021, 49(2): 354-361. DOI: 10.12263/DZXB.20200391.
Research on Prediction Algorithm of Landslide Deformation Based on SIMM-UKF and Resistivity Imaging Technology
The dynamic change of soil seepage field and its deep displacement are the main inducements of landslide geological disasters. To solve the problem that the existing deep displacement monitoring technology can not describe and explain the deformation process of landslide in space
an imaging prediction technology of landslide internal structure based on simplified interactive multiple model (SIMM) and unscented kalman filter (UKF) is proposed. Electrical prospecting has the characteristics ofcollecting underground media information quickly and accurately
Furthermore
it can realize multi-dimensional resistivity profile imaging. Based on the above and geological conditions
resistivity models collected by different exploration devices are taken as input. The threshold detection is used to judge whether the change speed of the resistivity value around the slip surface exceeds the warning value
and the data of each model are processed by unscented Kalman filter and output interactively. Field experiments show that the algorithm solves the problem of sensitivity matching between resistivity acquisition devices
realizes fast and multi-dimensional imaging of the internal structure of landslide geological body
and improves the effectiveness of interpretation of landslide internal deformation process.