Linear Control of Pipeline Bridge Construction Based on Optimized Grey Model
The traditional grey prediction model is easy to be disturbed by external noise in the prediction of bridge linear shape,which leads to the reduction of prediction accuracy.Therefore,Kalman filtering method is used to reduce the noise of bridge vertical displacement data,and the optimized grey prediction model is constructed.Based on a pipeline bridge project,by comparing the vertical displacement values predicted by the gray model before and after optimization with verified FEM simulations,the optimization effect of the Kalman filtering method on the traditional gray prediction model is proved.The results show that the difference between the predicted vertical displacement value calculated by the gray prediction model optimized by Kalman filtering method and the finite element simulation value is small,and the overall average error is about 12％,which is significantly improved compared with the prediction accuracy of the traditional gray prediction model.
pipeline bridgegrey modelKalman filtering methodfinite element analysislinear control
万方数据
维普
