Structural Health Monitoring Using Smart Sensors - ideals ...

damage/deterioration is intrinsically a local phenomenon. Therefore, to comprehend such
dynamic behavior, the motion of structures needs to be monitored by densely located
sensors at a sampling frequency sufficiently high to capture salient dynamic
characteristics.
1.2 SHM using smart sensors
When many sensors are implemented, wireless communication appears to be
attractive. The high cost associated with the installation of wired sensors (Celebi, 2002;
Farrar, 2001) can be greatly reduced by employing wireless sensors. Wireless sensors
often convert analog signals to digital signals prior to radio frequency (RF) transmission,
while many wired systems collect analog signals at one or several base stations where the
signals conversion takes place. The digital conversion on the wireless sensor node
eliminates possible signal degradation during analog signal communication through long
cables. Wireless sensor systems are, thus, promising as data acquisition systems with a
large number of sensors installed on sizable structures.
Being “smart”, i.e., having data processing capability in the sensors, is an essential
feature that further increases the potential of wireless sensors. Smart sensors can locally
process measured data and transmit only the important information through wireless
communication. As a network, wireless sensors extend the capability. For instance,
sensors that are malfunctioning in the network can be detected, and other sensors can
rebuild sensor topology without this dead node. As another instance, location mapping can
be done automatically by a localization service (Doherty et al., 2001; Kwon et al., 2005a;
Kwon et al., 2005b), which helps civil engineers determine and confirm the location of
large numbers of sensors on complex structures.
Smart sensors, however, have limited resources, prohibiting direct application of
traditional structural monitoring strategies. For example, the communication speed is too
slow to centrally collect all of the measured information. Clocks on sensor nodes are not
always synchronized. Some communication packets may be lost. Storage and memory
space is limited. Processor speed is slower than that of a PC. Smart sensors do not
necessarily offer a real-time system; programmers may not be able to assign appropriate
priority to given tasks. Moreover, battery power imposes limitations on many aspects of
smart sensors. Any task consuming large amounts of power becomes impractical on a
battery-operated smart sensor node. Smart sensor systems need to overcome these
limitations using deliberate system design, as seen in some of the time synchronization
and reliable communication research efforts (Ganeriwal et al., 2003; Maroti et al. 2004;
Mechitov et al., 2004).
From the perspective of SHM, being smart makes it feasible to monitor structural
response densely both in time and space. The amount of data generated from a monitored
structure can be enormous due to the large number of sensors and high sampling
frequency. For example, the Tsing Ma and Kap Shui Mun Bridges in Hong Kong produce
63 MB of data every hour (Wong, 2004). Being smart is expected to allow significant data
compression at the node level by extracting only the information necessary for the task at
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