京滨铁路沉降变形监测及其预测模型构建  

Construction of Settlement Deformation Monitoring and Prediction Model for the Jingbin Railway

作　　者：贾士楠 JIA Shi-nan(The 5th Engineering Co.,Ltd.of China Railway 18th Bureau Group,Tianjin 300450,China)

机构地区：[1]中铁十八局第五工程有限公司,天津300450

出　　处：《广东水利电力职业技术学院学报》2024年第4期34-38,共5页Journal of Guangdong Polytechnic of Water Resources and Electric Engineering

摘　　要：沉降变形会导致铁路运营安全性下降。通过沉降变形监测,可及时发现并解决潜在的安全隐患,保障铁路安全。对此,以京滨铁路沉降为例,研究其变形监测及其预测模型构建方法。将沉降观测桩作为监测设备,按沉降观测频次设置数据采集方案,采集监测点的沉降数据。以该数据为基础,采用曲线回归法构建预测模型,实现沉降预测。结果表明:预测总沉降变形值为-1.78 mm~1.97 mm;DK144+921断面测点不稳定;DK145+068、DK143+874测点连续下沉;其余测点稳定,在设计允许范围内。与基于IPSO-SVR的预测方法和基于WT-RF的预测方法相比,该研究法的均方根误差(RMSE)相对比更小,说明该法预测准确度更高。Settlement deformation can lead to a decrease in the operational safety of railways.By monitoring settlement deformation,potential safety hazards can be identified and resolved in a timely manner,ensuring the safety of railway operations.Therefore,the study focuses on the monitoring of settlement deformation and the construction of prediction models for the Beijing Binhai Railway.Using settlement observation piles as monitoring equipment,a data collection plan is set up according to the frequency of settlement observation to collect settlement data from monitoring points.Based on these settlement data,a prediction model is constructed using curve regression method to achieve settlement prediction.The results show that the predicted total settlement deformation value is-1.78mm~1.97mm,the measurement points of DK144+921 section are unstable,the measurement points of DK145+068 and DK143+874 are experiencing continuous subsidence,while the other measurement points are stable and within the design allowable range.Compared to prediction methods based on IPSO-SVR and WT-RF,the root mean square error(RMSE)of this studied method is relatively smaller,indicating higher prediction accuracy.

关 键 词：京滨铁路 沉降变形监测 曲线回归法 预测模型 

分 类 号：TP241.33[自动化与计算机技术—检测技术与自动化装置]