Research On The Surveying Data Quality Control Of High-speed Railway Track Control Network

To ensure that the high-speed train with high speeds can run safely and smoothly,the track must have high smoothness.As the precise control reference of railway track laying and maintenance,the track control network called base-piles control points III(CPIII)must be precise and reliable.The CPIII network has a large scale and a complex network structure,the complex factors such as observation data error,adjustment datum original data error and the lapping error between sectional surveying networks will affect the accuracy and reliability of control points,which will eventually affect the construction and evaluation of high smoothness of the track.On the basis of the existing technical specifications,with the goal of track smoothness control,to further improve the accuracy and reliability of the track control network surveying data,perfect the process control theory and technology system of HSR surveying data quality,and ensure the high-standard construction of HSR and the high-speed,stable and safe operation of trains,is a subject to be further explored in the theory of HSR surveying.The gross errors detection and identification is the main content of surveying data quality control.The mean shift model and variance expansion model,which take the least squares(LS)residual as the initial detection objects,can not solve the statistical problems of residual well,which is easy to cause a misjudgment of gross errors.Even if the L₁-norm estimation method with stronger ability to detect gross errors is used to CPIII network with a complex network structure,its robustness and reliability need to be verified.In addition to the observation data errors,the datum data errors caused by the scale inconsistency between CPI,CPII and CPIII networks and the movement of control points will affect CPIII network in the form of the original data error.However,the existing methods are difficult to effectively solve such datum data quality control and diagnosis problems.In addition,due to the influence of surveying error and adjustment datum design factors,there will be a lapping deviation between adjacent sections of CPIII network which is measured in segments and adjusted separately,and the control points with the same name in the overlapping area may also move due to construction damage and other reasons.However,the existing conventional lapping algorithm used in CPIII control network fails to take into account the influence of the deviation of the control network on track smoothness,and it lacks the sufficient theoretical foundation.In order to make up for the shortcomings of the existing track control network quality control technology,according to the actual needs of the construction and operation management of HSR,and drawing on the ideas of large systems cybernetics and multivariate quality control and diagnosis theory,the global data quality control system of CPIII(GDQCS-CPIII)is established.According to the major factors affecting the quality of surveying data and their function characteristics at different links,a global quality control strategy including two main levels(i.e.the quality control of subsystems and the coordination control among subsystems)is proposed,and the related theories and methods are studied.Gross errors detection of observations is one of the core contents of subsystem quality control.According to the guiding principle of detecting gross errors before LS adjustment and based on L₁-norm estimation,the reliability diagnosis technology of surveying data is studied.Specifically,the key technologies and methods such as the local analysis identification method(LAIM)for identifying the robustness failpoint in L₁-norm estimation(RFP-L₁),the L₁-norm estimation with regulatory factors(RF-L₁)for resisting the RFP-L₁gross errors and multiple gross errors detection algorithm based on RF-L₁(MGED-RF-L₁)are proposed.The gross error detectability and identifiability of observation is the premise of its gross error can be accurately identified.Aiming at the large amount of observations and complex structure of CPIII plane network,the relationship between two current separability analysis methods(i.e.,the methods that using correlation coefficient and gross errors judgment equations(GEJE)),and the superiority of the GEJE method for CPIII plane network are discussed.Then,using the GEJE method and synthetically utilizing the structural characteristics of CPIII plane network and the function model characteristics of the gross errors judgment equation,the matrix elementary transformation theory is used to mine and analyze the general regularity of the gross errors detectability and identifiability of CPIII plane network.The quality control and diagnosis of datum data is another core content of subsystem quality control after the gross errors detection of observations.Aiming at the problem that the CPIII plane network has unstable datum points and the datum data contains systematic errors,according to the characteristic that the spatial geometric configurations between datum points determined by the observation network and the prior coordinates of datum points are consistent,the datum data quality control and diagnostic method based on geometry of control network(DQCD-BG)is proposed.In addition,aiming at the incompatibility of datum points in elevation control network caused by datum point movement,an incompatible datum point identification method based on likelihood ratio(LR)test(ICDPI-LR)is also proposed.The smooth overlap between adjacent sections is the core to achieving the coordinated control between subsystems.In the process of lapping,the existing smoothing lapping methods fail to take into account the influence of the surveying control network on the track smoothness,and fail to consider the stability of the control points in lapping area.To this end,the principles of adjacent sections lapping should be followed for the situation that the new-built control network is measured in segments and adjusted separately,are put forward.Moreover,the surveying control network lapping algorithm considering the track ride comfort(CTRC-LP)is designed.Through the theoretical deduction,simulation and measured data analysis,the results show that:(1)The proposed reliability diagnostic technology of observations based on L₁-norm estiamation is used in CPIII control network,where the LAIM algorithm can accurately identify the RFP-L₁.The RF-L₁algorithm can transform the RFP-L₁into non-RFP-L₁observation,which is more robust than the classic L₁-norm estimation.The MGED-RF-L₁algorithm combines the advantages of the RF-L₁algorithm in resisting RFP-L₁gross error and the GEJE algorithm in considering the gross errors identification correlation between observations,so it can accurately identify the multiple gross errors,its result is more reliable than those of closed-loop search method,L₁-norm estimation and data snooping method.(2)The mathematical models of the correlation coefficient method and GEJE method are not only equivalent in the diagnosis of the gross errors separability between two outlier statistics,but also equivalent in the diagnosis of the gross errors identifiability of single observation.Moreover,for the problem of multiple gross errors separability diagnosis,the GEJE method has a stronger application possibility than correlation coefficient method,so the GEJE method is more suitable for the multiple gross errors detectability and identifiability analysis of CPIII plane network.The results of Monte Carlo experiments are consistent with the analysis results of the GEJE method,whch shows that the gross errors detectiability and identifiability regular pattern of CPIII plane network mined by GEJE method is correct.In CPIII control network,each observation has the ability to detect and identify gross errors,the maximum number of gross errors that can be detected and identified respectively in the six observations that measure the same target are three and two,the maximum number of gross errors that can be detected and identified respectively in the2n observations of one station are n and(n-1).(3)The DQCD-BG algorithm comprehensively considers the influence of projection deformation,instability of datum point and low precision of datum point on the control network adjustment.It effectively solves the datum data quality control problem of CPIII plane network when constructing the HSR survey coordinate system by Gauss zonal projection at present,which is more reliable than the traditional compatibility method.The ICDPI-LR algorithm overcomes the defect that the classical LR test can not be used for multiple incompatible datum points identification,and can accurately identify the incompatible datum points in CPIII vertical network.Moreover,the Quasi-Stable adjustment method is more helpful to ensure the height smoothness of CPIII elevation network after adjustment than the constrained adjustment method.(4)The CTRC-LP algorithm can effectively eliminate the connection deviation between adjacent sections of CPIII control network,and it is more helpful to ensure the high smoothness of the network after overlapping than both the collocation overlapping method and the constrained adjustment overlapping method.