DOI: 10.11908/j.issn.0253-374x.2019.11.006

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中图分类号: TU997


基金项目: 国家重点研发计划(2017YFC1500605),上海市科委(18DZ1201203)




A Condition Assessment Method for Bridges at Network Level Based on Multi-Source Information
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摘要:针对区域内既有桥梁，研究了路网桥梁结构的共性与个性特点，利用网级相关性总结规律并演绎推广，系统地提出了基于多源信息的桥梁网级评估与预测方法.对桥梁历史检测报告、监测评估报告、设计图纸等进行数据集成与规整，将提取的关键参数及数据集进行神经网络训练与验证，生成一系列桥梁构件及结构层的退化模型.考虑维修行为对结构性能的直接干涉作用，对路网区域范围内的桥梁群进行状态评估及退化趋势预测.以石家庄市高速路网历史数据为依托，通过算例验证了方法的系统性和有效性.



Abstract:This paper studied the commonality and personality of bridges at network level, summaried, and generalized the intrinsic rules according to their similar deterioration patterns. A network-level assessment and prediction method was proposed, for the first time, based on multi-source data. For large quantities of inspection reports, monitoring reports and bridge design drawings, the data integration and regulation process was conducted in order to extract key parameters and data sets applying to neural network of structures and components. A series of deterioration models were generated incorporating maintenance effects, based on which the condition assessment and deterioration prediction was realized for bridge populations. Based on the highway network in Shijiazhuang, an example was presented to verify the systematization and effectiveness of the proposed method for the purpose of bridge network management and decision-making.





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