Study On The Heavy Railway Subgrade Assessment System

In the course of operation in existing heavy rail, the ancillary of subgrade bed,embankments and retaining structures is increasing year by year. The safe of the existing lines is seriously affectted by these diseases. The status of existing lines roadbed is assessed, depending on first-hand subgrade data through on-site investigation, real-time monitoring, geophysical detection etc.. This is of great significance for routine maintenance and line capacity expansion. The studies on the state of the existing line is a little in our country. The evaluation methods is single, existing large empirical and subjective. In this paper, for the study Shuohuang rail, the Assessment System of existing heavy rail roadbed state,completed the following main aspects:The overall framework of subgrade assessment system (HRRAS) was established,according to modular design. The assessing sub-modules of subgrade bed,embankments,retaining structure and transition section were established respectively, making use of computer simulating expert mechanism. The4assessment model of Line, segment, mileage and local assessment was established. Based on analysis of subgrade deformation monitoring data, The3subgrade deformation warning mode of section mileage and local point was founded.The problem,the current technology assessment classification of roadbed being inadequate,the roadbed-technology-state-grading-stan dards of existing lines was customized,considering basic characteristics of roadbed-technology-state-grading and combined with the existing norms,engineering experience and other information. Compared with the existing norms,the assessment system was based on the results of system operation, reducing impact of subjective experience.The evaluation index hierarchy system was builted,including roadbed indicators,embankment indicators,bridge-road transition section indicators,culvert-road transition section indicators and supporting structure indicators of index system.According to the characteristics of evaluation indicators,the methods including the limit equilibrium theory, mathematical statistical theory and fuzzy neural network,was selected.The underlying parameters and evaluation criteria was also selected.The dual-index index evaluation model of safety factor and reliability was established for high embankment of exsiting line.The computational model of high embankment reliability was builted, making use of simplify Bishop method.Considering the fuzziness and randomness of calculation parameters, the fuzzy random reliability of calculation methods was established for embankment retaining structures. For example, The rigid pile of modeling ideas and parameter selection was described,and the feasibility of retaining structures embankment evaluation was demonstrated.The database of subgrade deformation prediction and evaluation based on long-term monitoring data was established by curve fitting method. The five predicted curve of hyperbolic exponential,Hoshino, Asaoka and parabola were selected.The functions of monitoring data and subgrade settlement prediction cross-sectional analysis was achieved. The early warning functions of "mileage" or "section" deformation was also achieved.According to characteristics of evaluation indicators including subgrade bed and embankment potential disease and subgrade bed capacity, the knowledge representation,the fuzzy membership function form and qualitative and quantitative data preprocessing way of three kind of evaluation indexs were studied. Combined with the level of division structure of evaluation index system, the evaluation function was achieved by programming the implementation.The existing heavy rail roadbed condition assessment system was achieved, applied VB programming language.According to subgrade field-testing and findings of the evaluation section, the evaluation parameters of Shuohuang railway subgrade was collected. The "section" subgrade state was assessed,making use of evaluation system. Meanwhile, some "point" we choosed were reinforced.Compared reinforcement before and after state, the reinforcing effect of the reinforcement means was judged. The results of the assessment was discussed, and the scientific of system was validated.