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.
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. 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. However, long sleep-cycles make the technology vulnerable to missing or misinterpreting the effect of a rare event. Current battery-powered wireless SHM methods use periodic sampling with relatively long sleep-cycles to increase a sensor's operational life. 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. Additionally, the technology has to interpret effects of rare, high-impact events like earthquakes or hurricanes. The next generation of bridge SHM technology needs to continuously monitor conditions and issue early warnings prior to costly repair or catastrophic failures. Louis, MO, United Statesĭeveloping a practical framework for long-term structural health monitoring (SHM) of large structures, such as a suspension bridge, poses several major challenges.
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