基于马尔可夫链-卡尔曼滤波法的拱坝变形预测

Prediction of arch dam deformation based on Markov Chain-Kalman filter method

变形监测分析和预警对大坝健康运行起着关键的作用,但是监测数据都不可避免地存在随机误差。卡尔曼滤波法可以有效地剔除测量数据中的噪声,然而,利用其对大坝未来的趋势位移做出预测时与实际情况吻合度不高。因此提出了马尔可夫链-卡尔曼滤波法,既能剔除测量数据噪声又可以准确的预测未来位移。利用浙江某拱坝位移实测资料,拟合并预测了该大坝的变形,验证结果表明该方法的拟合预测效果良好,可用于拱坝变形预测和安全监控。

Deformation monitoring and early warning analysis of the dam play a key role in the healthy operation of dam. However, there are unavoidable random errors in the monitoring data. Kalman filtering method can eliminate the noise from the observed data effectively;however, the prediction of the displacement trend of the dam does not agree well with the actual conditions using this method. In this paper, Markov chain-Kalman filter method was proposed, which can not only remove the random error but also predict the displacement accurately. Based on the observed displacement data of an arch dam in Zhejiang Province, the method showed an accurate prediction of dam deformation. Therefore, Markov chain-Kalman filter method can be used in the prediction of arch dam deformation and security monitoring.