Application of Kalman filtering to high and steep slope deformation monitoring prediction of open-pit mines
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摘要: 為了剔除GPS邊坡位移監測過程中的噪聲干擾,提高監測數據的有效性,特引入隨機線性卡爾曼濾波離散數學模型.以水廠鐵礦GPS邊坡監測數據為依據,利用該數學模型可以計算出各監測點每期變形量的濾波值和位移速度,并對各監測點下一期的變形量進行估算和預測.經實例驗證,卡爾曼濾波變形量與實際變形量有較好的一致性.Abstract: A discrete mathematical model based on random linear Kalman fihering is introduced to eliminate random disturbance noise in the process of GPS slope deformation monitoring and to improve the validity of monitoring data. On the base of GPS slope monitoring data in Shuichang Iron Mine, the filtering value of deformation and the velocity of displacement at each point in each stage can be calculated with the mathematical model and the slope deformation at each point in the next stage can be estimated and predicted. It is proved with an example that the deformation obtained by Kalman filtering is more approximate to the real slope deformation.
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Key words:
- Kalman filtering /
- GPS /
- slope deformation /
- data processing /
- displacement vector
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