The civil engineering community is becoming increasingly interested in monitoring structural behavior of civil infrastructure and in evaluation of the structural performance. The demand has largely been driven by deficiencies in structural performance due to the aging of the infrastructure, excessive loading, and natural disasters such as an earthquake, a landslide, a typhoon and a tsunami. In this study, a structural health monitoring methodology using acceleration responses is proposed for damage detection of a three-story prototype building structure during shaking table testing. A damage index is developed using the acceleration data and applied to outlier analysis, one of unsupervised learning based pattern recognition methods. A threshold value for the outlier analysis is determined based on confidence level of the probabilistic distribution of the acceleration data. The probabilistic distribution is selected according to the feature of the collected data.
Korea has constructed the safety management network monitoring test systems for the civil infrastructure since 2006
which includes airport structure, irrigation structure, railroad structure, road structure, and underground structure.
Bridges among the road structure include the various superstructure types which are Steel box girder bridge, suspension
bridge, PSC-box-girder bridge, and arch bridge. This paper shows the process of constructing the real-time monitoring
system for the arch bridge and the measured result by the system. The arch type among various superstructure types has
not only the structural efficiency but the visual beauty, because the arch type superstructure makes full use of the feature
of curve. The main measuring points of arch bridges composited by curved members make a difference to compare with
the system of girder bridges composited by straight members. This paper also shows the method to construct the
monitoring system that considers the characteristic of the arch bridge. The system now includes strain gauges and thermometers, and it will include various sensor types such as CCTV, accelerometers and so on additionally. For the long term and accuracy monitoring, the latest optical sensors and equipments are applied to the system.
This paper reports on test-bed for the long-term health monitoring system for bridge structures employing fiber Bragg
grating (FBG) sensors, which is remotely accessible via the web, to provide real-time quantitative information on a
bridge's response to live loading and environmental changes, and fast prediction of the structure's integrity. The sensors
are attached on several locations of the structure and connected to a data acquisition system permanently installed onsite.
The system can be accessed through remote communication using an optical cable network, through which the
evaluation of the bridge behavior under live loading can be allowed at place far away from the field. Live structural data
are transmitted continuously to the server computer at the central office. The server computer is connected securely to
the internet, where data can be retrieved, processed and stored for the remote web-based health monitoring. Test-bed
revealed that the remote health monitoring technology will enable practical, cost-effective, and reliable condition
assessment and maintenance of bridge structures.
A steady technology development of such high-tech sensor system as optical fiber sensor, GPS sensor and laser sensor
has led to increasingly utilizing them for monitoring the civil structure including the bridge. The state-of-the-art
monitoring system making a great commitment to improving the stability and accuracy of the system has been
effectively used for enhancing the efficiency of existing monitoring system. Optical fiber strain sensor, among those
high-tech sensors, functions to measure the strain of the members using a contact method, like the existing strain sensor,
because of the common characteristics of the strain sensors, but, compared to the existing electrical resistance strain
sensor, it proved to be less affected by temperature as well as able to effectively correct the effect by temperature itself.
The study, in an attempt to identify the temperature effect on FBG optical fiber strain sensor, among the sensors being
used to monitoring system in bridges, evaluated the data from
long-term measurement by real time monitoring system
using optical fiber strain sensors. To that end, the real time monitoring system using optical fiber sensors were installed
on Sapgyo Bridge (560m-long steel box girder composite bridge with maximum span of 80m) built in 1998 at Dang-jin,
South Choong-chung Province and the monitoring continued for a certain period. The optical fiber sensors used was
os310 of MOI (Micron Optic, Inc). The existing electrical resistance sensor was also set up under the same conditions for
the purpose of comparing the temperature effect. In the wake of the analysis, the effect by temperature on measurement
using optical fiber sensors under the condition of actual bridge could be identified.
As a first step for the safety network integration, test bed bridge was integrated by using the FBG sensor system. For the
operating efficiency of the bridge monitoring system, software which can control the conventional sensor system and
fiber optic sensor system concurrently was developed. Measuring item was limited to the strain, and the other measuring
items such as acceleration or displacement will be applied to the bridge next research period. Beside these items, image
processing device was installed to the test bed bridge, and the applicability of these data was considered. As a result of
strain measurement, the data from fiber optic sensor system were high stable and reliability, and the problems or
advanced parts will be suggested during the test bed bridge operation in the future.
Generally, the management criteria by monitoring items applied to the bridge management is decided through the
intuition of the based on the empirical data without any professional and systematic background. In this study, the span
deflection is selected among the bridge monitoring items and verify the appropriate management criteria in the case of
deflection by the laboratory test. Test specimens are the small-sizing bridge specimens which are made by reinforced
concrete. Those are classified by variation of span length and stiffness of section. As a result of test, the relationship
between the span center deflection and the safety level of bridge is suggested.
The rapid growth in the smart sensor technology (SST) has enabled easier and more economic construction of the
structural health monitoring system (SHM). Nevertheless, there is no distributed damage detection algorithm for efficient
usage of the computation power of the SST. Therefore, this study aims at developing a new distributed damage detection
algorithm suitable for the smart sensor system for the SHM. The algorithm suggested in this study utilizes the damping
ratio of a structure, using the structure's energy dissipation ratio. In other words, each smart sensor installed to the
structure analyzes the response signals from the structure into a damping ratio, which in turn is computed into an energy
dissipation ratio, using the smart sensor's ability to handle data. Thus, this method detects the damages and locations of
the damages in a structure using the changes in the energy dissipation ratio it has calculated. In this study proves the
usefulness of the developed energy dissipation ratio by numerical simulation.