路面日常养护巡查数据采集与时空演化分析

Pavement Daily Maintenance Inspection Data Collection and Time-Space Evolution Analysis

每周1~2次的外业巡查获得的病害数据,由于完整性与精细度的缺失,难以支持病害演化分析、风险排序与养护资源调配。文章首次提出以病害时空演化规律分析为核心的路面日常养护巡查数据采集和分析体系,以支持病害时空分析为设计导向,建立了整合病害时间和空间特性信息的新型日常巡查数据采集模组。提出了可实现病害时空演化规律研究的新型分析体系:空间上,根据不同路段病害数目的对比分析,确定病害频发路段;时间上,根据病害数目的变化,得到病害频发时段;根据单一病害影响范围的扩展,结合影像资料,得到单一病害演化规律,并为病害演化预测与风险评估提供依据;分析病害维修资料和已修补病害二次破坏数据,评价修补技术与材料耐久性能。进一步对病害大量产生的时段和路段、单一病害演化严重程度做出有效预测,从而评估病害风险,合理调度养护资源,实现高效率的养护管理决策。研究成果为日常养护巡查数据的采集、分析与应用提供参考。

China’s daily pavement maintenance obtains a large amount of disease data through field inspections 1-2 times a week.Due to the lack of data integrity and precision,it is difficult to support disease evolution analysis,risk ranking,and maintenance resource allocation.This paper presents for the first time a data collection and analysis system for road surface routine maintenance patrols centered on the analysis of the spatial and temporal evolution of the disease.First,with the support of the spatiotemporal analysis of the disease as a design guide,a new daily inspection data collection module integrating disease time and space characteristics information is established.Secondly,a new analysis system that can study the law of the spatiotemporal evolution of diseases is proposed.In space,according to the comparative analysis of the number of diseases in different sections,the sections with frequent diseases are determined.In terms of time,according to the change in the number of diseases,we can get a period of disease frequency.According to the extension of the influence scope of a single disease,the evolution rule of a single disease can be obtained by combining the image data,and the basis for disease evolution prediction and risk assessment can be provided.By analyzing the data of disease maintenance and secondary damage of repaired disease,the repair technology and durability of the material can be evaluated.Furthermore,it is possible to make effective predictions on the periods and road sections where a large number of diseases are generated,and the severity of the evolution of a single disease,to assess the risk of the disease,reasonably schedule maintenance resources,and achieve efficient maintenance management decisions.the research results provide a reference for the collection,analysis,and application of daily maintenance patrol data.