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This paper discusses issues of using wireless sensor systems to monitor structures and pipelines in the case of disastrous
events. The platforms are deployed and monitored remotely on lifetime systems, such as underground water pipelines. Although
similar systems have been proposed for monitoring seismic events and the structure health of bridges and buildings,
several fundamental differences necessitate adaptation or redesign of the module. Specifically, rupture detection in water
delivery networks must respond to higher frequency and wider bandwidth than those used in the monitoring of seismic
events, structures, or bridges. The monitoring and detection algorithms can also impose a wide range of requirements on
the fidelity of the acquired data and the flexibility of wireless communication technologies. We employ a non-invasive
methodology based on MEMS accelerometers to identify the damage location and to estimate the extent of the damage.
The key issues are low-noise power supply, noise floor of sensors, higher sampling rate, and the relationship among displacement,
frequency, and acceleration.
Based on the mentioned methodology, PipeTECT, a smart wireless sensor platform was developed. The platform was
validated on a bench-scale uniaxial shake table, a small-scale water pipe network, and portions of several regional water
supply networks. The laboratory evaluation and the results obtained from a preliminary field deployment show that such
key factors in the implementation are crucial to ensure high fidelity of the acquired data. This is expected to be helpful in
the understanding of lifeline infrastructure behavior under disastrous events.
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