卡尔曼滤波在大坝动态变形监测数据处理中的应用  

Application of Kalman filtering in data processing of dam dynamic deformation monitoring

作　　者：王利[1] 李亚红 刘万林[1] 

机构地区：[1]长安大学地质工程与测绘工程学院,陕西西安710054 [2]西安黑河供水有限责任公司,陕西西安710061

出　　处：《西安科技大学学报》2006年第3期353-357,共5页Journal of Xi’an University of Science and Technology

基　　金：中国地质调查局项目(200416000001)

摘　　要：详细地讨论了离散线性系统的卡尔曼滤波模型的建立及相应的精度评定公式,通过对某大坝动态变形监测数据的卡尔曼滤波处理和结果分析,发现卡尔曼滤波值、预报值与原始观测值数据曲线的变化趋势非常接近,说明所建立的卡尔曼滤波模型是合理的、可靠的,可以较好地模拟动态目标系统的变化规律。同时,卡尔曼滤波模型能够实时、快速地处理大量动态变形数据,并能有效地改善动态变形监测数据的精度。This paper discusses the establishment course of the Kalman filtering model of discrete and linear system, and the corresponding precision estimation formulas are put forward in the meantime. According to the Kalman filtering processing and the results analysis on the dynamic deformation monitoring data of a dam, the data curve changing tendency of the Kalman filtering results and the Kalman forecast results are very close to the initial observation data. It is also proved that the established Kalman filtering model is rational and reliable, and this discrete Kalman filtering model can appropriately simulate the law of physical variation of the dynamic object system. At the same time, this discrete Kalman filtering model can quickly and even in real time process large numbers of dynamic deformation monitoring data and improve the precision of the dynamic deformation monitoring data.

关 键 词：卡尔曼滤波 大坝 变形监测 数据处理 精度评定 

分 类 号：P207.2[天文地球—测绘科学与技术] TV698.1[水利工程—水利水电工程]