Research on Real-time Discriminating Method for the Gross Error in the 3D Control Network of High-speed Railway
The field observation of the 3D control network of the high-speed railway is affected by adverse environmental factors,which inevitably leads to measurement gross errors.In order to identify measurement errors earlier,timely supplement measurement,the real-time discrimination method for gross errors in the 3D control network was proposed to improve data quality and the accuracy of the 3D adjustment results.According to types and characteristics of control network,a detailed analysis was conducted on the types of closed loops,and a closed loop closure error of Class Ⅰ,Ⅱ,and Ⅲ was calculated.A closed loop closure error verification model was derived based on the law of covariance propagation,and the two times relative mean square error was used as the criterion for determining the quality of the data.The results show that,there are a strong regularity and symmetry in the shape of 3D control network.After rounding,it is recommended to use 1/7 000,1/13 000,and 1/23 000 as the limit errors for their corresponding closed loops.The method can distinguish and detect measurement errors in real-time during the field data observation process of the 3D control network,which is beneficial for on-site supplementary measurement at the minimum cost,thereby improving the data reliability and quality of the 3D control network.
high-speed railway3D control networkthe gross error eliminationcovarianceclosure error
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