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基于有序聚类不等分法的路面状况评价

Pavement Condition Evaluation Based on Ordered Clustering Inequality Method
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摘要 对于我国常将等长路段作为路段划分的基本单元的方法可能导致路面损坏状况指数的数值过高或过低、造成养护资源的浪费或路面使用质量下降等问题,根据有序聚类原理以及Fisher算法中损失函数的概念,将Fisher最优分割和传统有序聚类分析相结合的方法应用于路段划分。以病害类型统计矩阵为变量指标,对指标之间定义类直径的误差函数来判别最优分割,提出适用于路面的有序聚类二阶差分统计法来确定最优分类数。通过对工程实例的验证分析对比,基于有序聚类不等分的路面划分方法更能准确地反映水泥混凝土路面破损状况的局部变化,为水泥混凝土路面养护方案决策提供更科学的依据。 For China often equal length sections as the basic unit of the section division method may cause the value of PCI(Pavemant Surface Condition Index)is too high or too low,resulting in the waste of maintenance resources or pavement use quality decline and other problems,based on the principle of ordered clustering and the concept of loss function in Fisher's algorithm,the method of combination of Fisher optimal partition and traditional ordered clustering analysis is applied to road segmentation.The statistical matrix of disease types is used as the variable index,and the error function of class diameter is defined between the indexes to discriminate the optimal division,and the second-order difference statistics method of ordered clustering applicable to pavements is proposed to determine the optimal classification number,and the classification results are further improved according to the characteristics of cement concrete pavement maintenance in China.Through the comparison of testing and validation analysis of engineering examples,the pavement classification method based on ordered clustering unequal division can more accurately reflect the local changes of cement concrete pavement damage condition and provide a more scientific basis for the decision of cement concrete pavement maintenance scheme.
作者 夏晶 马杰灵 吴姗姗 XIA Jing;MA Jie-ling;WU Shan-shan(College of Architecture and Traffic Engineering,Guilin University of Electronic and Technology,Guilin,Guangxi 541000,China)
出处 《黑龙江交通科技》 2023年第11期1-4,10,共5页 Communications Science and Technology Heilongjiang
基金 桂林电子科技大学研究生教育创新计划资助项目(2021YCXS177)。
关键词 道路养护 路面评价 路段划分 有序聚类 road maintenance pavement evaluation road segmentation ordered clustering
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