应用时空复合趋势面Kriging方法插值地表沉降

Surface Settlement Interpolation Based on Composite Spatio-temporal Mean Trend Model Kriging Interpolation Method

通过布设监测点可反映地表沉降变化趋势,确保施工和运营期间安全,但沉降监测点数量有限,且易受施工作业、天气等因素干扰导致数据缺失或污染,因此需对监测区域数据进行插值处理。针对采用传统地统计插值方法估计地铁地表沉降趋势精度较低的问题,提出了一种基于时空复合趋势面的Kriging插值方法。以乌鲁木齐地铁3号线2017年6月24日—9月3日共15期地铁地表沉降观测值为实验数据,分别采用两种方法对沉降监测点缺失数据进行插补。结果表明,相较于传统方法,基于时空复合趋势面的Kriging插值方法的拟合精度更高,RMSE可降低约35%。

Deploying monitoring points can reflect surface settlement trend,which can ensure safety during construction and operation.However,the number of settlement monitoring points is limited and vulnerable to missing or contaminated data due to interference from construction,so the data in the monitoring area needs to be interpolated.We put forward a Kriging interpolation method based on composite spatio-temporal mean trend model to address the problem of low accuracy in estimating subway surface subsidence trends using traditional geostatistical interpola-tion methods.Taking a total of 15 weeks of subway surface subsidence observations from June 24 to September 3,2017 on Urumqi Metro Line 3 as experimental data,we used two methods to interpolate missing data for settlement monitoring points.The results show that compared with the traditional method,the Kriging interpolation method based on composite spatio-temporal mean trend model has higher fitting accuracy and the RMSE can be reduced by about 35%.