Civil Engineering Reference
In-Depth Information
147m
728 m
181 m
N14
S14
N12,13
North
South
S11
N10
68
79
91
9
93
87
87
93
93
91
79
102
S1
S12
S3
S5
S7
S9
N2,16
N4
N6
N11
N8
S2
S13
S4
S6
S8
S10
N1
N3,17
N5
N7
N9
N15
PFIG
Tri-axis accelerometer
Potentiometer
Climate station
Narada
server
Strain gage
UNIT= m
Fig. 8.1
Wireless sensor network deployment on the New Carquinez Suspension Bridge
Fig. 8.2
Installation details of the New Carquinez Suspension Bridge long-term monitoring system: (
a
) typical
Narada
wireless sensor node
beneath the deck girder in a magnetically mounted weather-proof enclosure; (
b
) small solar panel installed on the bridge top deck to power a
Narada
node; (
c
) string potentiometer at the deck-tower interface to measure longitudinal displacement
inexpensive single-board computer. The functionality of the server is to: (1) time synchronize the server clock using the
network time protocol (NTP); (2) time synchronize the wireless sensors in each sub-network using a beacon time
synchronization protocols previously developed for
Narada
; (3) command the wireless sensors to collect data; (4) locally
store data on the on-board hard drive; and, (5) communicate data to the Internet via a cellular modem. The servers can collect
data on either a schedule or upon user-demand; their default data collection occurs every 4 h with 8 min of bridge response
data collected.
A massive database server termed
SenStore
has been created off-site to store the data and to expose application
programming interfaces (APIs) to data clients seeking to use bridge data in their data processing algorithms.
SenStore
is a
data management system designed for structural health monitoring (SHM) applications [
4
]. It uses a relational database to
store bridge meta-data including structural component definitions, geometric details, sensor network data (e.g. sensor type
and installation location), and structural analysis information (e.g.
,
definitions needed for finite element modeling). Because
the massive amounts of raw time history data from sensors are ill-suited for storage in a traditional relational database, a
secondary database system based on the HDF5 file system is implemented in
SenStore
for the storage of sensor data. The
relational database links directly to the HDF5 file system so that queries for sensor data can be handled by the
SenStore
server through the relational database. The server-client model implemented in the design of
SenStore
allows secure access
to bridge data through a well-defined set of APIs. Computational tools are designed to perform autonomous system operation
and to undertake data analysis. Tools for tracking sensor operation (i.e., fault detection), data visualization, and modal
parameter extraction, among others, have been already created [
7
]. In this paper, the tools designed for automated modal
extraction are primarily used to process bridge data.
