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A Study on the Slope Failure Monitoring of a Model Slope by the Application of a Displacement Sensor

机译:置换传感器应用模型斜率的斜坡故障监测研究

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Many causalities and economic losses are caused by natural disasters, such as landslides and slope failures, every year. This suggests that there is a need for an early warning system to mitigate casualties and economic losses. Most of the studies on early warning systems have been carried out by predicting landslide-prone areas, but studies related to the prediction of landslide occurrence time points by the real-time monitoring of slope displacement are still insufficient. In this study, a displacement sensor and an Internet of Things (IoT) monitoring system were combined together, to monitor slope failure through cutting experiments of a real-scale model slope. Real-time monitoring of the slope movement was performed simultaneously via a low-cost, efficient, and easy-to-use IoT system. Based on the obtained displacement data, an inverse displacement analysis was performed. Finally, a slope instrumentation standard was proposed based on the slope of the inverse displacement for early evacuation before slope failure.
机译:许多因果关系和经济损失是由自然灾害,例如每年山体滑坡和斜坡故障引起的。这表明需要提前预警系统来减轻伤亡和经济损失。大多数关于预警系统的研究已经通过预测滑坡 - 俯卧区域来进行,但是与坡度位移的实时监测的对滑坡发生时间点的预测有关的研究仍然不足。在本研究中,将位移传感器和物联网(物联网)监控系统组合在一起,以通过切割实际模型斜率的切割实验来监测斜率故障。通过低成本,高效且易于使用的物联网系统同时进行对斜率运动的实时监控。基于所获得的位移数据,进行逆位移分析。最后,基于斜率故障前提前抽空的逆位移的斜率提出了斜坡仪表标准。

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