基于时间序列模型的青藏铁路路基变形预测

为分析青藏铁路路基高程不规则变形，通过建立高程—时间响应模型，基于Box-Jenkins建模方法，确定时间序列模型阶数，根据AIC准则，选取适合的时间序列模型，最后给出批量预测全部路基测点高程的算法步骤。研究了青藏铁路路基高程随时间变形规律问题。结果表明：以2010年—2018年每月青藏铁路K1425+050处左侧路基高程数据为例，建立了ARMA(2,1,1)模型，并以2019年数据作为验证集，模型通过了模型适应性检验，证明了模型的有效性和准确性；总结了青藏铁路沿线各测点至2023年12月预测值中可能出现重大变形以及测点左右两侧路基高程差值出现较大差值的10个危险点；在测点K1476+600附近，路基两侧出现明显长距离的差异。可见本模型能准确预测青藏铁路路基高程的变化，对于工程养护维修具有一定借鉴意义。

Prediction of Roadbed Deformation of Qinghai-Tibet Railway Based on Time Series Model

In order to analyze the irregular height deformation of the Qinghai-Tibet railway subgrade, by establishing an elevation-time response model, based on the Box-Jenkins modeling method, determine the order of the time series model, select a suitable time series model according to the AIC criterion, and finally give a batch forecast. The algorithm steps for measuring the elevation of subgrade points. The problem of the time-deformation law of the elevation of the Qinghai-Tibet railway subgrade is studied. The results show that: Taking the monthly elevation data of the left subgrade at K1425+050 of the Qinghai-Tibet Railway from 2010 to 2018 as an example, an ARMA (2,1,1) model was established, and the 2019 data was used as the validation set. The model passed the model The adaptability test proves the validity and accuracy of the model; it summarizes the possible major deformations in the predicted values of the measuring points along the Qinghai-Tibet Railway to December 2023 and the large differences in the elevation difference between the left and right sides of the measuring point. 10 dangerous points; around the measuring point K1476+600, there are obvious long-distance differences on both sides of the roadbed. It can be seen that this model can accurately predict the elevation change of the Qinghai-Tibet Railway subgrade, which has certain reference significance for engineering maintenance and repair.