卡尔曼滤波在大型深凹露天矿边坡变形监测预测中的应用  

Application of Kalman filtering to high and steep slope deformation monitoring prediction of open-pit mines

作　　者：李长洪[1,2] 范丽萍[1,2] 张吉良[1,2] 苗胜军[1,2] 王云飞[1,2] 

机构地区：[1]北京科技大学金属矿山高效开采与安全教育部重点实验室,北京100083 [2]北京科技大学土木与环境工程学院,北京100083

出　　处：《北京科技大学学报》2010年第1期8-13,共6页Journal of University of Science and Technology Beijing

基　　金：国家重点基础研究发展计划资助项目(No.2010CB731501;No.2010CB731506)

摘　　要：为了剔除GPS边坡位移监测过程中的噪声干扰,提高监测数据的有效性,特引入随机线性卡尔曼滤波离散数学模型.以水厂铁矿GPS边坡监测数据为依据,利用该数学模型可以计算出各监测点每期变形量的滤波值和位移速度,并对各监测点下一期的变形量进行估算和预测.经实例验证,卡尔曼滤波变形量与实际变形量有较好的一致性.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 moni- toring 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.

关 键 词：边坡变形 卡尔曼滤波 GPS 数据处理 位移矢量 

分 类 号：TD854.6[矿业工程—金属矿开采]