【作者】 李孝兵；

【导师】 连岳泉；

【作者基本信息】 武汉理工大学 ， 桥梁与隧道工程， 2006， 硕士

【摘要】 公路交通是国民经济、社会发展和人民生活服务的公共基础设施,是衡量一个国家国民经济实力和现代化水平的重要标志。随着社会经济的发展,公路交通量和交通荷载也在不断增加,公路路面结构普遍出现了不同程度的早期破损现象。因此,必须通过维修和技术改造等途径来提高其技术等级,延长使用寿命,而维修或技术改造的科学性和经济性则应建立在对现有公路路面使用性能的科学评价与预测的基础上。同时,只有对现有公路路面使用性能进行科学的评价及预测,才能从中发现路面工程在养护和管理中存在的不足和缺陷,从而有利于在工程建造的初期或使用过程中加以改善或控制。进一步完善路面使用性能评价和预测理论,对路面工程养护管理具有重要的指导意义。 本文通过对路面结构可能出现的各类复杂破损现象进行总结和分类,分析造成各种破损的原因;依据系统科学理论,确定表征路面结构使用性能的各个指标,并讨论各项指标的测定和分级标准:研究神经网络与遗传算法各自的特点,建立结合两者优点的遗传神经网络模型;将遗传神经网络引入到公路路面使用性能评价与预测,建立基于遗传神经网络的公路路面使用性能评价与预测模型,为公路路面使用性能的评价与预测提供科学方法,为路面管理系统提供依据。 结合上海市全市公路中的国道、省道和县道(不包括乡道和专用公路),通过对影响公路路面结构使用性能因素的分析,选取适当指标,运用建立的遗传神经网络模型,根据2002年至2004年历年的路面状况指数、行驶质量指数、路面强度指数和路面抗滑系数四个指标与路面质量指数之间的关系,对2005年的路面进行评价,得到的结果与实际的检测结果十分吻合,表明该模型很好的模拟了四个指标与路面质量指数之间复杂的关系;另外根据历年路面状况指数、行驶质量指数、交通量状况、维修的长度和面积五个指标与道路维修养护费用的关系,运用训练好的模型,对上海市各区公路署2006年的所需的养护资金进行了预测,通过对预测结果的分析,表明建模思路和方法可行,可为路面养护提供有力的指导和帮助。更多还原

【Abstract】 Highway transportation is a nationally public foundation facility which provides service for our society, and represents the modernization level of the whole social development and the real national economy strength. Along with the social economic development, as the increase of volume traffic and heavy load, highway has widely appeared damaged phenomenon. Therefore, in order to prolong its service life, we should take some measures such as maintain and improve its quality based on technique to improve its grade. The pavement performance is defined as an ability to guarantee all vehicles to transport normally and safely. The driving comfort and vehicles’ engine performance are affected directly by its capability, and the road transportation quality is also determined by its quality. At the same time, we could find out the inside shortage existed in the management of the road engineering, it also benefits to take into improvement or control in engineering construct and perfect the theory of road construction in initial or using stage.This text introduced various breaks and damages that may appear in highway and then analyzed the results of the diseases, studied the index of the pavement and discussed the measurement of various index and its rating standard. Based on the complementation of advantages of neural network and genetic algorithm, we established the GANN(genetic algorithm and neural network) model and then used the model to evaluate and forecast the pavement performance of the road.Through the state highway road, provincial highway and the county road (excluding township road and dedicated road) in Shanghai, we analyzed the factors that impact the pavement performance of the road and chose the appropriate indicators to establish a genetic neural network models. According to the relationship of the pavement condition index (PCI), road quality index (RQI), surface strength index (SSI), sideway-force coefficient (SFC) and the pavement quality index (PQI) from 2002 to 2004, we used this model to evaluate the pavement performance of the road in 2005, the test results and the actual results are very consistent. This model shows very good simulation between the four indicators and the quality of road;moreover, according to the relationship between the cost of road maintenance and pavement conditions index, road quality index, traffic conditions, the length and area of maintenance in road every year, we used the tested training model to forecast the conservation of funds in each district of highway department of shanghai in 2006, the results of the forecast indicated that this ideas and methods were feasible, this model could provide effective guidance and help to the maintenance of road.更多还原