Quasi-Self-Powered Piezo-Floating-Gate Sensing Technology for Continuous Monitoring of Large-Scale Bridges
Quasi-Self-Powered Piezo-Floating-Gate Sensing Technology for Continuous Monitoring of Large-Scale Bridges
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DOI：
10.3389/fbuil.2019.00029
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发表时间：
2019-03-26
影响因子：
3
通讯作者：
Chakrabartty, Shantanu
中科院分区：
文献类型：
--
作者：
Aono, Kenji;Hasni, Hassene;Chakrabartty, Shantanu
开发一个实用的框架，长期结构健康监测（SHM）的大型结构，如悬索桥，提出了几个主要的挑战。下一代桥梁SHM技术需要持续监测条件，并在昂贵的维修或灾难性故障之前发出早期预警。此外，该技术还必须解释地震或飓风等罕见的高影响事件的影响。由于世界上许多桥梁的设计使用寿命即将结束，因此这项技术的开发已经成为一个更高的优先事项。当前电池供电的无线SHM方法使用具有相对长的休眠周期的周期性采样来增加传感器的操作寿命。然而，长时间的睡眠周期使这项技术容易错过或误解罕见事件的影响。为了解决这些实际问题，我们提出了一种新型的准自供电传感解决方案，用于大型桥梁的长期和经济有效的监测。我们提出的方法结合了我们以前报道和验证的自供电压电浮栅（PFG）传感器与超低功耗，远程无线接口。PFG操作背后的物理原理使其能够连续捕获并在非易失性存储器中存储关于桥的动态负载条件的本地累积信息。使用广泛的数值和实验室研究，我们证明了PFG传感器预测结构条件的能力。然后，我们提出了一个系统级的设计，适应PFG传感SHM的桥梁。大型桥梁中SHM的一个挑战性方面是需要长距离无线询问，因为结构的许多部分不容易连续检查，并且桥梁的部分不能经常停止使用。我们表明，通过将自供电PFG传感器与小型电池和优化的远程有源无线接口相结合，我们可以实现准自供电系统，轻松实现超过20年的连续工作寿命。以西半球最长的跨锚碇悬索桥--美国密歇根州麦基诺大桥为例，验证了该方法的有效性和可行性。从部署的相关数据进行了讨论，除了局限性，挑战，以及广泛的现场部署拟议的SHM框架的额外考虑。
Developing a practical framework for long-term structural health monitoring (SHM) of large structures, such as a suspension bridge, poses several major challenges. The next generation of bridge SHM technology needs to continuously monitor conditions and issue early warnings prior to costly repair or catastrophic failures. Additionally, the technology has to interpret effects of rare, high-impact events like earthquakes or hurricanes. The development of this technology has become an even higher priority due to the fact that many of the world's bridges are reaching the end of their designed service lives. Current battery-powered wireless SHM methods use periodic sampling with relatively long sleep-cycles to increase a sensor's operational life. However, long sleep-cycles make the technology vulnerable to missing or misinterpreting the effect of a rare event. To address these practical issues, we present a novel quasi-self-powered sensing solution for long-term and cost-effective monitoring of large-scale bridges. The approach we propose combines our previously reported and validated self-powered Piezo-Floating-Gate (PFG) sensor in conjunction with an ultra-low-power, long-range wireless interface. The physics behind the PFG's operation enable it to continuously capture and store local, cumulative information regarding dynamic loading conditions of the bridge in non-volatile memory. Using extensive numerical and laboratory studies, we demonstrate the capabilities of the PFG sensor for predicting structural conditions. We then present a system level design that adapts PFG sensing for SHM in bridges. A challenging aspect of SHM in large-scale bridges is the need for long-range wireless interrogation, as many portions of the structure are not easily accessible for continual inspection and portions of the bridge cannot be frequently taken out-of-service. We show that by combining self-powered PFG sensors with a small battery and optimized long-range active wireless interface, we can realize a quasi-self-powered system that easily achieves a continuous operating lifespan in excess of 20 years. The efficiency and feasibility of the proposed method is verified in a case study of the Mackinac Bridge in Michigan, the longest suspension bridge across anchorages in the Western Hemisphere. Associated data from the deployment are discussed, in addition to limitations, challenges, and additional considerations for widespread field deployment of the proposed SHM framework.