摘要
位移作为地下水位、雨量、地声等影响因素综合作用的结果,是滑坡体滑动的直接表现。本文提出了Kalman滤波数据融合技术,建立了基于位移参数的Kalman滤波数据融合预测模型,利用Kalman滤波方法对多个位移监测数据进行滤波融合处理,对滑坡体的稳定状态和变化趋势做出更准确的预测。并将该技术应用于京港澳高速公路某滑坡体的变形分析与预测,对该滑坡体的四个位移传感器数据进行了Kalman滤波分析,结果表明,融合后的位移量估计精度更高,融合后的滤波数据更能准确地反映滑坡体的整体变形趋势,为滑坡后期施工及处治提供依据。
As the results of the impact factors of groundwater level,rainfall,earthquake sound and other ingredients coacting,displacement is the most direct performance of the slide in landslide mass. In this paper,the data fusion technology of Kalman-filter has been proposed,and establishing the prediction models of Kalman-filter data fusion based on displacement parameter,then utilizing the method of Kalman aimed to filtering-fusion process the data of displacement on several monitoring sites to make more accurate prediction on the stable state and changing tendency of landslide. By using this technology in the analysis and prediction of a landslide deformation of Jing Gang＇Ao freeway,the result of Kalman filter carried on in four displacement sensors shows that the measurement accuracy is improved greatly after fusion,and the fused filter data can accurately reflect the overall deformation of landslide,then providing the basis for the late construction and processing of landslide.
出处
《中国地质灾害与防治学报》
CSCD
2015年第4期30-35,42,共7页
The Chinese Journal of Geological Hazard and Control
基金
湖南省科技计划项目高新技术产业发展专项(S2014X503011)
湖南省交通科技计划项目(201423)
中国铁路总公司科技研究开发计划项目(2014G005-B)
湖南省住房和城乡建设厅科技计划项目(BZ201408
BZ201411)
住房城乡建设部2015年工程建设标准规范制订
修订计划项目(2015-1-100)
