KEYWORDS: Sensor networks, Sensors, Data modeling, System identification, Clocks, Energy efficiency, Matrices, Data transmission, Computing systems, Wireless communications
Embedded computation in wireless sensor networks (WSN) can extract useful information from sensor data in a fast and
efficient manner. Embedded computing has the benefit of saving both bandwidth and power. However, computational
capability often comes at the expense of power consumption on the wireless sensor node. This is an especially critical
issue for battery powered wireless sensor nodes. By developing a hybrid network consisting of wireless units optimized
for sensing interspersed with more powerful computationally focused units, it is now possible to build a network that is
more efficient and flexible than a homogeneous WSN. For this project, such a network was developed using Narada
units as low-power sensing units and iMote2 units as ultra-efficient computational engines. In order to demonstrate the
capabilities of such a configuration a network was created to extract structural modal parameters based on Markov
parameters. This paper validates the performance of the heterogeneous WSN using a laboratory structure tested under
impulse loading.
A dense network of sensors installed in a bridge can continuously generate response data from which the health and
condition of the bridge can be analyzed. This approach to structural health monitoring the efforts associated with
periodic bridge inspections and can provide timely insight to regions of the bridge suspected of degradation or damage.
Nevertheless, the deployment of fine sensor grids on large-scale structures is not feasible using wired monitoring
systems because of the rapidly increasing installation labor and costs required. Moreover, the enormous size of raw
sensor data, if not translated into meaningful forms of information, can paralyze the bridge manager's decision making.
This paper reports the development of a large-scale wireless structural monitoring system for long-span bridges; the
system is entirely wireless which renders it low-cost and easy to install. Unlike central tethered data acquisition systems
where data processing occurs in the central server, the distributed network of wireless sensors supports data processing.
In-network data processing reduces raw data streams into actionable information of immediate value to the bridge
manager. The proposed wireless monitoring system has been deployed on the New Carquinez Suspension Bridge in
California. Current efforts on the bridge site include: 1) long-term assessment of a dense wireless sensor network; 2)
implementation of a sustainable power management solution using solar power; 3) performance evaluation of an
internet-enabled cyber-environment; 4) system identification of the bridge; and 5) the development of data mining tools.
A hierarchical cyber-environment supports peer-to-peer communication between wireless sensors deployed on the
bridge and allows for the connection between sensors and remote database systems via the internet. At the remote
server, model calibration and damage detection analyses that employ a reduced-order finite element bridge model are
implemented.
Bridges undergo dynamic vehicle-bridge interaction when heavy vehicles drive over them at high speeds. Traditionally,
analytical models representing the dynamics of the bridge and vehicle have been utilized to understand the complex
vehicle-bridge interaction. Analytical approaches have dominated the field due to the numerous challenges associated
with field testing. Foremost among the challenges is the cost and difficulties associated with the measurement of two
different systems, i.e. mobile vehicle and static bridge. The recent emergence of wireless sensors in the field of
structural monitoring has created an opportunity to directly monitor the vehicle-bridge interaction. In this study, the
unrestricted mobility of wireless sensors is utilized to monitor the dynamics of test vehicle driving over a bridge. The
integration of the mobile wireless sensor network in the vehicle with a static wireless monitoring system installed in the
bridge provides a time-synchronized data set from which vehicle-bridge interaction can be studied. A network of
Narada wireless sensor nodes are installed in a test truck to measure vertical vibrations, rotational pitching, and
horizontal acceleration. A complementary Narada wireless sensor network is installed on the Geumdang Bridge
(Icheon, Korea) to measure the vertical acceleration response of the bridge under the influence of the truck. The
horizontal acceleration of the vehicle is used to estimate the position trajectory of the truck on the bridge using Kalman
filtering techniques. Experimental results reveal accurate truck position estimation and highly reliable wireless data
collection from both the vehicle and the bridge.
Concrete pipelines are one of the most popular underground lifelines used for the transportation of water resources.
Unfortunately, this critical infrastructure system remains vulnerable to ground displacements during seismic and
landslide events. Ground displacements may induce significant bending, shear, and axial forces to concrete pipelines
and eventually lead to joint failures. In order to understand and model the typical failure mechanisms of concrete
segmented pipelines, large-scale experimentation is necessary to explore structural and soil-structure behavior during
ground faulting. This paper reports on the experimentation of a reinforced concrete segmented concrete pipeline using
the unique capabilities of the NEES Lifeline Experimental and Testing Facilities at Cornell University. Five segments of
a full-scale commercial concrete pressure pipe (244 cm long and 37.5 cm diameter) are constructed as a segmented
pipeline under a compacted granular soil in the facility test basin (13.4 m long and 3.6 m wide). Ground displacements
are simulated through translation of half of the test basin. A dense array of sensors including LVDT's, strain gages, and
load cells are installed along the length of the pipeline to measure the pipeline response while the ground is incrementally displaced. Accurate measures of pipeline displacements and strains are captured up to the compressive and flexural failure of the pipeline joints.
Seismic damage to buried pipelines is mainly caused by permanent ground displacements, typically concentrated in the
vicinity of the fault line in the soil. In particular, a pipeline crossing the fault plane is subjected to significant bending,
shear, and axial forces. While researchers have explored the behavior of segmented metallic pipelines under permanent
ground displacement, comparatively less experimental work has been conducted on the performance of segmented
concrete pipelines. In this study, a large-scale test is conducted on a segmented concrete pipeline using the unique
capabilities of the NEES Lifeline Experimental and Testing Facilities at Cornell University. A total of 13 partial-scale
concrete pressure pipes (19 cm diameter and 86 cm long) are assembled into a continuous pipeline and buried in a loose
granular soil. Permanent ground displacement that places the segmented concrete pipeline in compression is simulated
through the translation of half of the soil test basin. A dense array of sensors including linear variable differential
transducers, strain gauges, and load cells are installed along the length of the pipeline to measure its response to ground
displacement. Response data collected from the pipe suggests that significant damage localization occurs at the ends of
the segment crossing the fault plane, resulting in rapid catastrophic failure of the pipeline.
The installation of a structural monitoring system on a medium- to large-span bridge can be a challenging undertaking
due to high system costs and time consuming installations. However, these historical challenges can be eliminated by
using wireless sensors as the primary building block of a structural monitoring system. Wireless sensors are low-cost
data acquisition nodes that utilize wireless communication to transfer data from the sensor to the data repository.
Another advantageous characteristic of wireless sensors is their ability to be easily removed and reinstalled in another
sensor location on the same structure; this installation modularity is highlighted in this study. Wireless sensor nodes
designed for structural monitoring applications are installed on the 180 m long Yeondae Bridge (Korea) to measure the
dynamic response of the bridge to controlled truck loading. To attain a high nodal density with a small number (20) of
wireless sensors, the wireless sensor network is installed three times with each installation concentrating sensors in one
portion of the bridge. Using forced and free vibration response data from the three installations, the modal properties of
the bridge are accurately identified. Intentional nodal overlapping of the three different sensor installations allows mode
shapes from each installation to be stitched together into global mode shapes. Specifically, modal properties of the
Yeondae Bridge are derived off-line using frequency domain decomposition (FDD) modal analysis methods.
Piezoelectric materials have received considerable attention from the smart structure community because of their potential use as sensors, actuators and power harvesters. In particular, polyvinylidene fluoride (PVDF) has been proposed in recent years as an enabling material for a variety of sensing and energy harvesting applications. In this study, carbon nanotubes (CNT) are included within a PVDF matrix to enhance the properties of PVDF. The CNT-PVDF composite is fabricated by solvent evaporation and melt pressing. The inclusion of CNT allows the dielectric properties of the PVDF material to be adjusted such that lower poling voltages can be used to induce a permanent piezoelectric effect in the composite. To compare the piezoelectric characteristics of the CNT-PVDF composite proposed, scanning electron microscope (SEM) images were analyzed and ferroelectric experiments were conducted. Finally, the aforementioned composites were mounted upon the surface of a cantilevered beam to compare the voltage generation of the CNT-PVDF composite against homogeneous PVDF thin films.
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