Abstract
In this paper, to guarantee that the train can take measures to reduce the damage caused by the earthquake, it propose an irregular GI S curve fitting based high-speed railway earthquake influence range calculation model. Firstly, this model eliminates the abnormal points, calculates feature points and finds demarcation points of the high- speed railway GI S curve to get the processed point collection in Mercator coordinate. Secondly, though usin g the processed point collection, this model applies least square polynomial segmentation fitting method to implement complex high-speed GI S curve fitting. Thirdly, calculate the earthquake influence rang on high-seed railway line, according to the scope of the earthquake equation and the high-speed railway GI S curve fitt ed equation. Finally, the paper selects the Beijing So uth to Dezhou East high-speed railway section which is part of Beijing-Shanghai line as a case study, which proves that the model can calculate the earthquake influence scope on the railway line offering decision support for train operation to ensure safety.
Highlights
By the end of 2016, China's total mileage of h igh-speed railway was more than 20,000 kilo meters [1, 2], accounted for over 60% of the world's total mileage of high speed railway, which ranked first in the world
The main process of curve discretizat ion of h igh-speed railway lines is easy to produce abnormal points and lose feature points, which are caused by the system error o r random select ion of high-speed railway GIS curve points, leading to the coordinate points deviate fro m the correct position gravely
Irregular GIS curve fitting of high-speed railway line is to select the appropriate type of fitting method to the coordinate points
Summary
By the end of 2016, China's total mileage of h igh-speed railway was more than 20,000 kilo meters [1, 2], accounted for over 60% of the world's total mileage of high speed railway, which ranked first in the world. The discretizat ion of high-speed railway lines’ GIS curve mainly through the direct method and the indirect method for the data acquisition [6]. Both ways use a finite number of coordinate points to characterize the railway line but without a mathematical equation to represent. The main process of curve discretizat ion of h igh-speed railway lines is easy to produce abnormal points and lose feature points, which are caused by the system error o r random select ion of high-speed railway GIS curve points, leading to the coordinate points deviate fro m the correct position gravely.
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