基于ARMA模型的隧道变形预测及参数估计分析OA
Deformation Prediction and Parameter Estimation of the Tunnel Based on ARMA Model
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 pro-cess 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 reason-able 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.
刘君伟;杨晓辉
北京京港地铁有限公司,北京 100068北京市建设工程质量第三检测所有限责任公司,北京 100037||北京市市政工程研究院,北京 100037
交通运输
地铁隧道ARMA模型变形预测时间序列
metro tunnelsAuto Regressive Moving Average(ARMA)modeldeformation predictiontime series
《市政技术》 2024 (007)
54-60 / 7
评论