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Metro vehicle of quick-speed wheeling extreme highly require rail planeness. And metro tunnel is structure to load-supporting vehicle wheeling, its construction is slender, great flexible degree, when its construction subject to unbalance force, partial slender tunnel easily changes of the form, makes a lot of changes to line shape of rail and affect operation of vehicle. It has grave actual purpose to research sedimentation monitoring of tunnel construction. This paper mainly study as follows contents about sedimentation monitoring of tunnel construction:(1) Generalize multiform factors of influencing settlement of metro tunnel. According to itself features of metro tunnel, discuss means of layout and measuring about settlement monitoring reference net, sedimentation monitoring of tunnel construction and treatment of monitoring data, and giveing one example about settlement monitoring of tunnel construction of Nanjing Metro NO1, specificly expound settlement monitoring of metro tunnel construction.(2) Analyse adjustment reference and itself access of monitoring reference net. Mainly research some analysis methods about stabilization of monitoring reference net based on same reference, including method of inspection of tolerance, t inspection method, average clearance inspection method, blocking clearance inspection method, and based on monitoring data of tunnel construction settlement monitoring reference net of Nanjing Metro NO1, individually use upward methods to inspect stabilization of single-point and global net.(3) Synthetically expound grey system theory and building mode, feature of mode , and treating method of data. Majorly study building process of GM(1,1) mode and algorithm circuit.(4) Represent basic axiom of nerural net, mainly including mode structure, transfer function, learning regulation and training way. Detailed discuss concept, mode, basic fabric, nerve unit mode and algorithm process of BP neural network.(5) Study modelling thought, network configuration, majorize GNNM(1,1) mode method and learning algorithm of GNNM(1,1) mode combined grey system theory and neural network. Based on tunnel construction settlement monitoring of Nanjing Metro NO1, simulate and forecast monitoring data by GM(1,1) mode and GNNM(1,1) mode.
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