Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors

Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors
复制标题

DOI:
10.3390/s18124480
复制
发表时间:
2018-12-01
期刊:
影响因子:
3.9
通讯作者:
Spencer, Billie F., Jr.
Spencer, Billie F., Jr.
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Fu, Yuguang;Hoang, Tu;Spencer, Billie F., Jr.

文献摘要

被引文献

相似文献

无线智能传感器(WSS)已被提出作为一种有效的手段,以减少有线结构健康监测系统的高成本。然而,民用基础设施的许多损坏情况涉及突发事件,例如强烈地震,这可能在几秒钟内导致损坏甚至故障。无线监视系统通常采用占空比来降低功耗;因此,如果它们在事件发生时处于节能睡眠模式,则它们将错过这样的事件。本文开发了一种基于需求的WSS,以满足突发事件监测的要求,最小的功率预算和低响应延迟,而不牺牲高保真测量或丢失关键信息的风险。在建议的WSS中,可编程的基于事件的开关实现利用低功耗触发加速度计的开关集成在一个高保真传感器平台。特别地,该方法可以在突发事件发生时快速开启WSS,并且从低功率加速度测量无缝地过渡到高保真数据采集。通过实验室和现场试验,验证了所提出的WSS的能力。结果表明,该方法能够有效地捕捉到突发事件的发生,为结构状态评估提供高保真数据。
Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even failure in a matter of seconds. Wireless monitoring systems typically employ duty cycling to reduce power consumption; hence, they will miss such events if they are in power-saving sleep mode when the events occur. This paper develops a demand-based WSS to meet the requirements of sudden event monitoring with minimal power budget and low response latency, without sacrificing high-fidelity measurements or risking a loss of critical information. In the proposed WSS, a programmable event-based switch is implemented utilizing a low-power trigger accelerometer; the switch is integrated in a high-fidelity sensor platform. Particularly, the approach can rapidly turn on the WSS upon the occurrence of a sudden event and seamlessly transition from low-power acceleration measurement to high-fidelity data acquisition. The capabilities of the proposed WSS are validated through laboratory and field experiments. The results show that the proposed approach is able to capture the occurrence of sudden events and provide high-fidelity data for structural condition assessment in an efficient manner.