基于双曲线模型的卡尔曼滤波法在建筑物沉降预测中的应用

Application of Kalman Filter Method Based on Hyperbolic Curve Model in the Settlement Forecast of Building

利用最小二乘法求出双曲线模型的模型参数,将此参数看作带有动态噪声的状态向量,建立基于双曲线模型的卡尔曼滤波模型,对建筑物的沉降量进行预测。卡尔曼滤波过程中,模型的参数不断发生变化,增强了其适应观测数据的能力,从而减小了拟合误差。计算表明,用基于双曲线模型的卡尔曼滤波模型对建筑物的沉降量进行预测,误差较小,效果较为理想。

We construct the hyperbolic curve model and then use the least square method to obtain its parameters.These parameters are regarded as state vectors to contain dynamic noises to erect a Kalman filter model based on the hyperbolic curve model.On the basis of this model we forecast settling amounts of the building.Since the parameters of the Kalman filter model change continuously,its ability to suit the observation data is increased,and the fitting error of the model is reduced.An example of calculation shows that the forecast error is small,and this suggests that it is best to use the Kalman filter model based on the hyperbolic curve model to forecast settling amounts of the building.