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首页> 外文期刊>International journal of online engineering >De-noise of Online Monitoring Basic Data Collected by Surveying Robots
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De-noise of Online Monitoring Basic Data Collected by Surveying Robots

机译:测量机器人在线监测基本数据的降噪

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Abstract Three-dimensional online monitoring systems based on a surveying robot (TCA2003) are widely used in the slope monitoring of various open pits. A lot of noise is contained in basic monitoring data (azimuth, vertical angle, distance) because of various factors. Thus, the accuracy of basic monitoring data is greatly reduced, and this issue has become a limitation in landslide warning. In this paper, multi-cycle monitoring data from multiple open pits are used as data source and de-noised using different filtering methods. At the same time, filtering effect is evaluated using the image and accuracy of filtered basic data. Best filtering methods of different monitoring basic data are proposed, laying the foundation for automated processing of monitoring data based on a surveying robot.
机译:摘要基于勘测机器人的三维在线监测系统(TCA2003)被广泛用于各种露天矿的边坡监测。由于各种因素,基本监视数据(方位角,垂直角度,距离)中包含大量噪声。因此,基本监测数据的准确性大大降低,这个问题已成为滑坡预警的局限性。本文将来自多个露天矿的多周期监测数据用作数据源,并使用不同的滤波方法对其进行去噪。同时,使用图像和已过滤基本数据的准确性来评估过滤效果。提出了不同监测基础数据的最佳过滤方法,为基于测量机器人的监测数据自动化处理奠定了基础。

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