文章摘要
时间序列模型在桥梁健康监测数据预测中的应用
Application of Time Series Model in Prediction of Bridge Health Monitoring Data
投稿时间:2018-06-08  修订日期:2018-06-08
DOI:
中文关键词: 桥梁  健康监测  时间序列模型  挠度  预测
英文关键词: Bridge  Health Monitoring  Time Series Model  Deflection  Prediction
基金项目:中央高校基本科研业务费资助项目(310821161120);重庆市科委社会民生项目(cstc2017shmsA30022);重庆市公路局交通科技项目“中型桥梁适用性安全监测系统及评估技术研究与应用”;
作者单位E-mail
陆萍 重庆交通大学 土木工程学院 583921237@qq.com 
王涛 重庆交通大学 土木工程学院 411942528@qq.com 
韦跃 江苏交科交通设计研究院有限公司 411942528@qq.com 
李竞 重庆市沙坪坝区公路养护中心 411942528@qq.com 
吴海军 重庆交通大学 土木工程学院 583921237@qq.com 
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中文摘要:
      桥梁监测数据的分析是健康监测研究的重点及难点问题。为了从采集到的海量数据中分析得到反映桥梁健康状况及发展趋势的结果,可利用时间序列模型的预测功能,对其发展变化进行预测。本文分析了时间序列预测模型的应用特点、分析流程及其建模过程。以江津长江大桥为例,建立了时间序列预测模型,对其挠度监测数据进行了分析及预测,通过预测数据与实测数据相比,结果表明时间序列模型具有较高的预测精度和可行性,可为桥梁健康监测分析提供有益的借鉴。
英文摘要:
      The analysis of bridge monitoring data is a key and difficult issue in health monitoring research. In order to analyze the results of reflecting the health status and development trend of the bridge from the collected mass data, the prediction function of the time series model can be used to predict its development and change. This paper analyzes the application characteristics, analysis process and modeling process of the time series forecasting model. Taking the Jiangjin Yangtze River Bridge as an example, a time series forecasting model was established and its deflection monitoring data was analyzed and predicted. Compared with the measured data, the results show that the time series model has higher prediction accuracy and feasibility. Provide a useful reference for bridge health monitoring and analysis.
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