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Method to Improve the Accuracy of Slope Monitoring Data Based on a Measuring Robot

机译:基于测量机器人的边坡监测数据精度提高方法

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To improve the accuracy of slope monitoring data based on a measuring robot, an effective and viable correction method is proposed. A 3D monitoring system based on a measuring robot and Geomos is utilized to collect data. The monitoring data of 44 cycles of Dagushan and Yanqianshan open-pit iron mines in Anshan City are employed as the data source. Large amounts of data are calculated and compared, and a quantitative analysis of various factors that influence the accuracy of measuring robot is performed. Data calculation shows that the proposed mathematical meteorological correction model and directional deviation correction method can effectively improve the accuracy of measuring robot. The corrected data can accurately represent the displacement of monitoring points, which provides important real-time warning of open-pit slope landslides. Methods to improve the accuracy of measuring robot are studied to increase data reliability. The nature of the data and the factors that affect the quality of data are analyzed.
机译:为了提高基于测量机器人的边坡监测数据的准确性,提出了一种有效可行的校正方法。利用基于测量机器人和Geomos的3D监控系统来收集数据。以鞍山市大孤山,延千山露天铁矿44个循环的监测数据为数据源。计算并比较大量数据,并对影响测量机器人精度的各种因素进行定量分析。数据计算表明,提出的数学气象校正模型和方向偏差校正方法可以有效提高测量机器人的精度。校正后的数据可以准确地表示监测点的位移,从而为露天斜坡滑坡提供重要的实时预警。研究了提高测量机器人精度的方法,以提高数据可靠性。分析了数据的性质和影响数据质量的因素。

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