基于北斗的地基沉降监测方法研究与实现
首发时间:2018-10-19
摘要:由于时代和科技的不断发展与进步,桥梁、铁塔等建筑都开始大规模修建,而地下资源不断地开发和利用引起的建筑走形、建筑开裂、局部坍塌等问题将会严重影响社会的可持续发展甚至威胁到人们的生命及财产安全。本文研究并实现了一种基于低成本北斗接收机的地基沉降监测方法,首先利用中位值递推平均滤波对经过网络RTK定位的较高精度数据进行数据平滑预处理,然后利用最小二乘多项式曲线拟合与中位值递推平均滤波的融合算法实现对桥梁的地基高程数据进行时间域内超高精度观测,观测精度可达0.0005m,最后利用无损卡尔曼滤波实现对于地基沉降趋势的预测,预测精度可达0.00001m。这样能更加精确地提前预测出桥梁的沉降趋势,避免重大安全事故发生。
关键词: 导航、制导与控制 网络RTK定位 最小二乘曲线拟合 中位值递推平均滤波 无损卡尔曼滤波
For information in English, please click here
Research and implementation of Foundation Settlement algorithm
Abstract:With the continuous development and progress of science and technology in the times. Construction of bridges, towers and other bulidings began to be built on a large scale. The sustainable development of society and the safety of people\'s life and property would be seriously affected by the continuous development and utilization of underground resources, such as the shape of the building, the cracking of the building, and the local collapse. A high precision positioning of monitoring method of foundation settlement based on low sink BD receivers was studied and realized. First, accurate precision data from network RTK was treated smoothly by recursive average filtering of the median value. Then ultra high precision ground data was observed which a fusion algorithm based on recursive median filtering between curve fitting and median value was proposed. The accuracy of observation can reach 0.0005m. Finally, the unscented kalman filter is used to predict the settlement of the bridge. The prediction accuracy can reach 0.00001m. So the settlement trend of the bridge can be predicted accurately and avoiding major accidents.
Keywords: Navigation guidance and control Network RTK positioning Least square curve fitting Unscented Kalman Filter
引用
No.****
动态公开评议
共计0人参与
勘误表
基于北斗的地基沉降监测方法研究与实现
评论
全部评论0/1000