基于测量机器人的实时粗差探测方法研究

Researchon real-time gross error detection method based on georobot

粗差探测是变形监测中一项重要的工作。随着全站仪技术的发展,测量机器人越来越多的应用到变形监测项目中,需要对获取的实时数据进行实时粗差探测。本文以Grubbs准则为基础探索了一种基于历史数据的实时粗差探测方法。经某电站实测数据测试表明,该方法可以识别出测量机器人返回数据中的粗差,同时解决观测值正常变化被识别为粗差的问题。

Gross error detection is an important work in deformation monitoring.With the development of total station technology,more and more georobots are applied to deformation monitoring projects.It is necessary to detect gross errors of real-time data obtained by measuring robots.Based on Grubbs criterion,this paper explores a real-time gross error detection method based on prior data.The test of the measured data of a power station shows that this method can identify the gross errors in the real-time data obtained by the measuring robot,and solve the problem that the normal changes of the observed values are identified as gross errors.