摘要
以北京市海淀区某地铁站一体化棚户区改造项目为例,运用ARMA模型对高层建筑盖挖逆作法施工过程中邻近既有地铁隧道变形进行预测。以既有地铁隧道沉降实时监测数据为原始数据集,对原始数据集进行适当插补处理后,通过极大似然估计法对模型进行参数估计,给出了模型关键参数,构建了合理的预测模型。将模型预测结果与实测数据进行对比,显示预测结果与实测数据变化趋势高度吻合,充分验证了预测模型的可行性、有效性与稳定性。
Taking a shantytown renovation project of a subway station in Haidian District,Beijing as an example,the ARMA model is used to predict the deformation of the adjacent existing subway tunnel during the construction process of the top-down excavation method for high-rise buildings.The real-time monitoring data of the settlement is taken as the original data set to appropriate interpolation process of the original data set.The parameters of the model are estimated by the maximum likelihood estimation method to give the key parameters of the model,and a reasonable prediction model is constructed.By comparing the model prediction results with the measured data,it is shown that the prediction results are highly consistent with the change trend of the measured data,which fully verifies the feasibility,effectiveness and stability of the prediction model.
作者
刘君伟
杨晓辉
Liu Junwei;Yang Xiaohui(Beijing Jinggang Metro Co.,Ltd.,Beijing 100068,China;Beijing Construction Engineering Quality No.3 Testing&Inspection Institute,Beijing 100037,China;Beijing Municipal Engineering Research Institute,Beijing 100037,China)
出处
《市政技术》
2024年第7期54-60,共7页
Journal of Municipal Technology
关键词
地铁隧道
ARMA模型
变形预测
时间序列
metro tunnels
Auto Regressive Moving Average(ARMA)model
deformation prediction
time series
