Application of Time Series Analysis in the Analysis and Forecasting of Track Geometry Status

Abstract

Track geometry deformation lead to dangerous of train driving, endangering railway transport. It is the prerequisite of developing a reasonable plan of track maintenance and repair that find out the occurrence of track geometry deformation and the law of development. It is also one of the core works of railway's maintenance and repair. In this paper, we analyze detect data of railway track use time series analysis, discovery the track deformation production, make a thorough inquiry to find out the trend of deformation occurrence and forecast the status of the track geometry. The results show that there is higher accuracy of the forecasting, and it can be used to guide the conservation of railway track.

Forecasting Damage Mechanics by Deep Learning

“…There are numerous applications of time series forecasting in computational mechanics. Jia et al [Jia, Xu and Wang (2010)] studied the track geometry status forecast for developing track maintenance and repair plan. Kulkarni et al [Kulkarni, Dhoble and Padole (2018)] applied this method into the wind speed forecast and turbine blade fatigue analysis.…”