基于桥梁挠度长期监测值的动态预测

文章针对重庆高家花园嘉陵江大桥实时健康监测系统的挠度长期监测数据,根据监测信息的时间序列呈季节、循环等非平稳状态特点,介绍采用ARMA时间序列预测模型,对挠度监测数据中所包含的外荷载的变化趋势及结构抗力的衰变信息进行动态预测,同时建立了结构外效应的预测函数。结果表明,采用低阶模型能对挠度监测值进行较好的动态预测。

Dynamic Prediction Based on Long-term Monitoring Data of Bridge Deflection

According to Chongqing Gaojiahuayuan Jialing Bridge Health Monitoring System Real-time long-term monitoring data, and the time series of monitoring information which were in the season and the cycle non-stationary state, we brought into use ARMA time series prediction model.ARMA time series prediction model performed dynamic forecast for the external load and decay information of structural resistance in the monitoring dataset.At the same time, the model established the structure prediction function.The result shows that low-end model can be well used to predict the monitor value of the deflection.