Husain Syed Faizan, Abbas Mohammad Shoaib, Wang Han, Qamhia Issam I A, Tutumluer Erol, Wallace John, Hammond Matthew
Department of Civil & Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Tensar International Corporation, Alpharetta, GA 30009, USA.
Sensors (Basel). 2024 Apr 25;24(9):2733. doi: 10.3390/s24092733.
This paper introduces a novel approach to measure deformations in geomaterials using the recently developed 'Smart Pebble' sensors. Smart Pebbles were included in triaxial test specimens of unbound aggregates stabilized with geogrids. The sensors are equipped with an aggregate particle/position tracking algorithm that can manage uncertainty arising due to signal noise and random walk effects. Two Smart Pebbles were placed in each test specimen, one at specimen's mid-height, where a geogrid was installed in the mechanically stabilized specimen, and one towards the top of the specimen. Even with simple raw data processing, the trends on linear vertical acceleration indicated the ability of Smart Pebbles to assess the geomaterial configuration and applied stress states. Employing a Kalman filter-based algorithm, the Smart Pebble position coordinates were tracked during testing. The specimen's resilient deformations were simultaneously recorded. bender element shear wave transducer pairs were also installed on the specimens to further validate the Smart Pebble small-strain responses. The results indicate a close agreement between the BE sensors and Smart Pebbles estimates towards local stiffness enhancement quantification in the geogrid specimen. The study findings confirm the viability of using the Smart Pebbles in describing the resilient behavior of an aggregate material under repeated loading.
本文介绍了一种使用最近开发的“智能卵石”传感器测量土工材料变形的新方法。智能卵石被放置在用地格栅加固的未结合集料的三轴试验试件中。这些传感器配备了一种集料颗粒/位置跟踪算法，该算法可以处理由于信号噪声和随机游走效应而产生的不确定性。每个试验试件中放置两个智能卵石，一个位于试件的中间高度，在机械稳定试件中安装了土工格栅的位置，另一个靠近试件顶部。即使进行简单的原始数据处理，线性垂直加速度的趋势也表明智能卵石能够评估土工材料的配置和施加的应力状态。在测试过程中，采用基于卡尔曼滤波器的算法跟踪智能卵石的位置坐标。同时记录试件的弹性变形。还在试件上安装了弯曲元件剪切波换能器对，以进一步验证智能卵石的小应变响应。结果表明，在土工格栅试件中，弯曲元件传感器和智能卵石对局部刚度增强量化的估计结果非常一致。研究结果证实了使用智能卵石描述集料材料在重复加载下弹性行为的可行性。
