论文部分内容阅读
路面管理和维护是道路工程的一个重要方面,因此在选择路面养护措施时,应该充分考虑路面的病害类型及经济性。在接缝式水泥混凝土路面中,横向接缝错台是一个关键问题,很大程度上影响行车舒适性和路面平整度。影响接缝错台的因素有很多,如交通荷载、路面结构、气候条件、路面龄期等。而基层状况是其中的一个重要因素,其对水泥混凝土路面的早期性能和长期性能的影响都很大。该研究采用人工神经网络法(ANNs)和多元线性回归法(MLR)预测接缝错台,对于研究中的路面龄期和不同基层类型等参数取值采用路面长期性能研究计划(LTPP)中的数据。研究结果表明:ANNs能够准确地预测接缝式水泥混凝土路面的接缝错台,除个别误差外其复判定系数(R2)很高。
Pavement management and maintenance is an important aspect of road engineering, so pavement maintenance measures should be taken into full consideration of the type of road disease and economy. In the seams of cement concrete pavement, the horizontal seam staggered is a key issue, largely affect driving comfort and road surface roughness. There are many factors that affect the fault location of joints, such as traffic load, pavement structure, climatic conditions and pavement age. The grassroots situation is one of the important factors, which have great influence on the early performance and long-term performance of cement concrete pavement. In this study, artificial neural network (ANNs) and multiple linear regression (MLR) were used to predict the joint fault location. For the parameters of pavement age and different grassroots types in the study, the long-term performance study (LTPP) data. The results show that: ANNs can accurately predict the joint displacement of the seamed cement concrete pavement, and its complex judgment coefficient (R2) is very high except for some errors.