摘要
变形监测分析的模型与方法主要是针对单点时序的分析,建立大坝位移自回归模型可实现大坝位移预测预报,但传统自回归模型都是针对单测点进行的,这意味着需要对所有的测点进行建模,将会造成大量模型冗余.而大坝作为一个整体结构,测点间的位移在空间上是相互关联的。单点自回归模型并未考虑着这种相关性,为了考虑测点间的这种空间相关性并建立统一的模型,本文采用时空自回归方法对五强溪大坝位移监测数据进行整体分析,建立了大坝位移的时空自回归模型。通过对大坝引张线测点的建模与预测分析,结果表明时空自回归模型在时间和空间上都可以对位移监测数据序列进行较好的拟合与预测。
Models and methods of analysis for deformation monitoring are always set for the time series data of one monitoring point.An auto-regressive model can be used for modeling dam deformation to forecast the displacement.In the traditional method,it is necessary to establish the auto-regressive model for every monitoring point.To some extent,the traditional method has to model different models for every monitoring point on the dam which make us do the same thing many times.However,as a whole structure,monitoring points on a dam are related to each other.The traditional time auto-regressive model does not consider the relationship between different monitoring points on the dam.To consider the spatial correlation between measuring points and thereby establish a unified model,a space-time auto-regressive method is used to model the displacements of the Wuqiangxi dam.Spacetime auto-regression is just used once for all the monitoring points on the dam which save time of processing space-time series.By analyzing and forecasting the horizontal displacements of the dam,our test results show that a space-time auto-regressive model can be used for fitting and forecasting displacement series both in the temporal and spatial domains.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2015年第7期877-881,共5页
Geomatics and Information Science of Wuhan University
基金
国家973计划资助项目(2013CB733303)~~
关键词
时空相关性
时空自回归模型
变形分析
temporal and spatial correlation
space-time auto-regressive model
deformation analysis