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重载铁路路基状态评估系统研究
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摘要
既有重载铁路在使用过程中,基床、路堤、支挡等附属结构的病害逐年增多,严重影响了既有线路的安全使用。通过对现场调查、实时监测、物探检测等方法获得的第一手路基资料的处理,进行既有线路路基的状态评估,对于线路的日常维护和扩能改造具有十分重要的意义。目前,我国既有重载线路路基状态评估的研究较少,评估方法单一,经验性和主观性较大。本文以朔黄铁路为研究对象,进行既有重载铁路路基状态评估系统研究,主要完成了以下几方面内容:
     建立既有线路路基状态评估系统HRRAS的总体框架。系统按模块化设计,利用计算机模拟专家的决策机理,分别对基床、路堤、支挡、过渡段建立评估子模块,形成线路、区段、里程、评估点4级评估模式,并在路基变形监测数据的分析和预测的基础上,建立区段、里程、评估点三级路基变形预警模型。
     针对目前路基状态评估中技术状态等级划分研究不足的问题,在考虑路基技术状态等级划分的基本特征的同时,结合现有规范、工程经验等资料,定制了切实可行的既有线路路基技术状态等级评定标准。与现有规范相比,该评定体系以系统运算结果为依据,降低了人为主观经验对评估结果的影响。
     建立了具有层次结构的评估指标体系:包括基床指标体系、路堤指标体系、路桥过渡段指标体系、路涵过渡段指标体系和支挡结构稳定性评估指标。根据评估指标的特点选取包括极限平衡理论、数理统计理论、模糊神经网络在内的计算方法。
     针对既有线路高填方路堤,建立以安全系数和可靠度指标双指标评价模式,以简化Bishop法建立高填方路堤可靠度计算模型。针对路堤支挡结构,建立考虑计算参数模糊性和随机性的模糊随机可靠度计算方法,并以刚性抗滑桩为例,阐述建模思路和参数选取,论证其在路堤支挡结构评估中的可行性。
     采用曲线拟合法,建立基于长期监测数据的路基变形预测与评估的数据库存储平台,选取双曲线法、指数曲线、星野法、Asaoka法、抛物线法等5种拟合预测曲线。实现了既有监测数据分析、路基横断面沉降预测分析、纵断面路基沉降预测分析、“里程”或“区段”变形预警等功能。
     根据基床潜在病害评估指标、基床承载力指标、路堤潜在病害评估指标的具体特征,研究了在评估系统中该三类评估指标的知识表示形式、有关的模糊化隶属度函数形式、定性和定量指标数据预处理的方式。然后结合评价指标体系的层次划分结构,通过编程实现该评估功能。应用VB程序语言编制既有重载铁路路基状态评估系统软件
     通过现场路基检测试验和评估区段路基调查结果,对评估区段的朔黄铁路路基评估参数进行采集,利用评估系统对评估“区段”路基状态进行评估。同时,通过对某工点加固前和加固后路基状态的评估对比,对加固效果进行评判,对评估结果进行讨论,验证了系统的科学性。
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.
引文
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