Structural Health Monitoring Using Smart Sensors - ideals ...

different type of sensors connected to separate nodes cannot be combined. The inability of
this approach to incorporate spatial information limits its effectiveness.
Gao (2005) proposed a Distributed Computing Strategy (DCS) for SHM that offers a
scalable approach that can incorporate spatial information. This DCS approach, based on
the DLV method (Bernal, 2002), does not need to centrally collect and analyze the
measurement data. Instead, the DCS shares data among the neighboring nodes to utilize
spatial information. Due to this local data sharing with limited numbers of neighboring
nodes, the total amount of data to be transmitted throughout the network is kept modest.
Therefore, this SHM strategy is scalable to a large number of sensors densely deployed
over large structures. While the DCS does not require measurements at all the DOFs, the
method’s performance improves with the number of DOFs measured. Computer analysis
and experimental validation on a simulated wireless network showed the DCS is a
promising SHM scheme. This strategy, however, has not yet been implemented on smart
sensors and experimentally verified.
Data loss during wireless communication is also problematic for SHM applications.
Wireless communication suffers from packet loss unless lost packets are resent. Kurata et
al. (2004) reported data loss during shake table experiments. Many civil engineering
applications using smart sensors do not address this data loss problem. Some of them
simply ignore lost data while others coincidentally receive all the packets during
experiments. However, SHM methods developed so far assume that data acquired at
sensors are available for data processing at the base station. The influence of lost data on
structural analysis has not been clearly investigated. Mechitov et al. (2004) employed a
reliable communication protocol to address this problem. Because acknowledgment
packets are sent frequently, the communication speed is slower than communication
without acknowledgment. Reliable communication services suitable to transfer large
amount of data is expected to advance SHM applications employing smart sensors.
The communication range of smart sensors is usually shorter than the size of civil
infrastructure. Centrally collecting data or sending commands to smart sensor nodes on
structures involves multihop communication. A routing path usually needs to be
determined prior to multihop communication (Mechitov et al., 2004). If a communication
path between two arbitrarily selected nodes is required, a very large table to store routing
paths needs to be constructed on each sensor node. Application-specific knowledge on
communication, such as collecting data to a sink node and dissemination, potentially
simplifies routing. Once paths are found, multihop communication can be started. Routing
path, packet structure, overhead information, etc. need to be carefully designed.
3. Time synchronization
Dynamic analyses of structures assume that data is synchronized, which is not the
default case with smart sensor networks. As described in section 2.2, several
synchronization protocols have been proposed. Some of them have synchronization
accuracy as good as tens of microseconds. However, the requirement of SHM on time
synchronization accuracy is not studied. Based on the fact that natural frequencies of
structures used in analyses are usually below 10 Hz, civil engineers may erroneously think
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