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Smart Pebble for Monitoring Riverbed Sediment Transport

机译:智能卵石监测河床沉积物的运输

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The smart pebble (SP) has been developed to monitor sediment transport in riverbeds. The implementation employs small size and low-cost acceleration and angular motion sensors. In this paper, we focus on calibration and testing of the final version of the SP, as well as its packaging in a 4-cm diameter spherical package. Error analysis of the sensors as well as the whole system has been modeled to evaluate the performance of the final system's outputs. The calibration was done in two separate stages: individual sensor calibration and overall system calibration. The complete SP unit was tested under linear motions generated by a shake table, and 2-D rotational motions using two manually controlled servomotors. Offline signal conditioning was done in MATLAB. Errors due to misalignment and gravity have been reduced. Experiments conducted by sampling a 1-Hz sinusoidal signal at different rates show that to keep the amplitude errors of the system under 5%, the sampling rate has to be at least ten times the maximum bandwidth of the signals acquired from the sensors. The SP has been tested in a real flume and the results show that the system provides enough accuracy in measuring its own accelerations as it moves inside the flume.
机译:开发了智能卵石(SP)来监控河床中的泥沙输送。该实现采用小尺寸和低成本的加速度和角运动传感器。在本文中,我们专注于SP最终版本的校准和测试,以及其直径为4厘米的球形包装中的包装。对传感器以及整个系统的误差分析进行了建模,以评估最终系统输出的性能。校准分两个阶段进行:单个传感器校准和整个系统校准。在振动台产生的线性运动和使用两个手动控制的伺服电机进行的二维旋转运动下,对完整的SP单元进行了测试。离线信号调理是在MATLAB中完成的。减少了由于未对准和重力引起的错误。通过以不同的速率对1 Hz正弦信号进行采样的实验表明,要使系统的幅度误差保持在5%以下,采样率必须至少是从传感器获取的信号最大带宽的十倍。 SP已在真实的水槽中进行了测试,结果表明,该系统在水槽内部移动时可提供足够的精度来测量其自身的加速度。

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