Combining GPS and BDS technology to monitor the deformation of long-span railway bridges with stricter deformation control requirements is of significance to the safety and control of the bridge and the safety of rail...Combining GPS and BDS technology to monitor the deformation of long-span railway bridges with stricter deformation control requirements is of significance to the safety and control of the bridge and the safety of railway traffic.Previous studies have ignored the influence of coloured noise in the deformation time series.This is not conducive to accurate deformation analysis of long-span railway bridges.Therefore,GPS,BDS and GPS/BDS monitoring data of Ganjiang Bridge located in Ganzhou city,Jiangxi Province,China are adopted in this paper to filter the coloured noise in the deformation time series by principal component analysis(PCA),and the influence of coloured noise on the deformation analysis results of railway bridge is analysed.The experimental results show that the diurnal temperature difference causes the mid-span and the tower of the railway cable-stayed bridge to deform with a period of about one day in the vertical and longitudinal directions,respectively.Ignoring colored noise will make the uncertainty of the deformation parameter estimation overly optimistic.PCA can significantly reduce the coloured noise,and thus reduce the uncertainty of deformation parameter estimation by about 73%.Moreover,the average difference between the daily periodic motion amplitudes of the monitoring points obtained by using GPS and BDS deformation time series is 1.65 mm.The use of GPS/BDS deformation time series is not only helpful to reduce the influence of coloured noise,but also can reduce the difference between amplitude analysis results obtained from GPS and BDS deformation time series.展开更多
基金the National Key Research and Development Program under Grant 2021YFB2600400the Science And Technology Project For China Railway Construction Corporation Limited under Grant 2022-A 02,Wuhan Enterprise Technology Innovation Project under Grant 2019010702011314+4 种基金Guangxi Science And Technology Plan Project under Grant AD19110107Guangxi Natural Science Foundation under Grant 2018GXNSFBA050006the Project To Improve The Basic Research Ability Of Young And MiddleAged Teachers In Guangxi Universities under Grant 2020KY06032Urban Spatial Information Engineering Beijing Key Laboratory Funded Project under Grant number 2020217Natural Science Foundation of Hubei Province under Grant 2020CFB282,National Natural Science Foundation of China under Grant 42264004.
文摘Combining GPS and BDS technology to monitor the deformation of long-span railway bridges with stricter deformation control requirements is of significance to the safety and control of the bridge and the safety of railway traffic.Previous studies have ignored the influence of coloured noise in the deformation time series.This is not conducive to accurate deformation analysis of long-span railway bridges.Therefore,GPS,BDS and GPS/BDS monitoring data of Ganjiang Bridge located in Ganzhou city,Jiangxi Province,China are adopted in this paper to filter the coloured noise in the deformation time series by principal component analysis(PCA),and the influence of coloured noise on the deformation analysis results of railway bridge is analysed.The experimental results show that the diurnal temperature difference causes the mid-span and the tower of the railway cable-stayed bridge to deform with a period of about one day in the vertical and longitudinal directions,respectively.Ignoring colored noise will make the uncertainty of the deformation parameter estimation overly optimistic.PCA can significantly reduce the coloured noise,and thus reduce the uncertainty of deformation parameter estimation by about 73%.Moreover,the average difference between the daily periodic motion amplitudes of the monitoring points obtained by using GPS and BDS deformation time series is 1.65 mm.The use of GPS/BDS deformation time series is not only helpful to reduce the influence of coloured noise,but also can reduce the difference between amplitude analysis results obtained from GPS and BDS deformation time series.
