Measure Dry Beach Length of Tailings Pond Using Deep Learning Algorithm

Jun Yang, Yeqing Sun, Qing Li, Zhiyu Qian
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引用次数: 5

Abstract

The length of dry beach determines the safety and stability of tailings dam. In order to measure the dry beach length more accurately, we put forward a method of measuring the dry beach length of tailings dam based on deep learning. This method is carried out in three steps:(1) installing monitoring cameras on both sides of tailings dam. (2) training the network model based on Mask R-CNN algorithm, identify waterline and outputs waterline coordinates. (3) measuring the length of dry beach by video screen in real time through inputting the waterline coordinates into the functional relationship between waterline coordinates and measured values. The results show that this model can accurately measure the length of dry beach, and is suitable for the conditions of insufficient illumination, blurred image, rain and snow.
利用深度学习算法测量尾矿库干滩长度
干滩长度决定了尾矿坝的安全性和稳定性。为了更准确地测量干滩长度,我们提出了一种基于深度学习的尾矿坝干滩长度测量方法。该方法分三步实施:(1)在尾矿坝两侧安装监控摄像机。(2)基于Mask R-CNN算法训练网络模型,识别水线并输出水线坐标。(3)通过视频屏幕实时测量干滩长度,将水线坐标输入到水线坐标与实测值的函数关系中。结果表明,该模型能准确测量干滩长度,适用于光照不足、图像模糊、雨雪等条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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