摘要
针对高层建筑物沉降预测模型精度低、与实测值不符等问题,提出了基于时序SAR技术的高层建筑物沉降变形预测方法。论文阐述了高层建筑物沉降观测技术流程,对水准控制网及水准观测路线等数据进行了分析。基于时序SAR技术预测模型是利用PSI算法在沉降观测结果中获取高层建筑物沉降中的形变数据,通过平差计算,结合BP神经网络构建高层建筑物沉降变形模型,实现沉降变形预测。实验结果表明,该方法降低了预测误差,精度较高,时序SAR技术在高层建筑沉降变形监测中的应用具有重要意义。
Considering the problems of low precision and large error in the measured value of the existing high-rise building settlement prediction model,this paper proposes a method based on time series SAR technology.Firstly,the technical process is described,and the key calculations such as leveling control network and leveling observation route are analyzed.Based on the prediction model of time series SAR technology,the PSI algorithm is mainly used to obtain the deformation information in the settlement observation results of high-rise buildings,and the settlement deformation prediction model is built by combining the free network adjustment calculation with BP neural network.The experimental results show that the method reduces the prediction error and has high prediction accuracy.It realizes the effective application of time series SAR technology in highrise building settlement monitoring,and is of great significance to related research.
作者
徐飞
XU Fei(Zhejiang Academy of Surveying and Mapping Science and Technology,Hangzhou 311101,China)
出处
《江西测绘》
2023年第2期4-7,19,共5页
JIANGXI CEHUI
关键词
时序SAR技术
高层建筑物
沉降观测
预测模型
Temporal SAR Technology
High Rise Buildings
Settlement Observation
Prediction Model
