The steel cables in long span bridges such as cable-stayed bridges and suspension bridges are critical members which
suspend the load of main girders and bridge floor slabs. Damage of cable members can occur in the form of crosssectional
loss caused by fatigue, wear, and fracture, which can lead to structural failure due to concentrated stress in the
cable. Therefore, nondestructive examination of steel cables is necessary so that the cross-sectional loss can be detected.
Thus, an automated cable monitoring system using a suitable NDE technique and a cable climbing robot is proposed. In
this study, an MFL (Magnetic Flux Leakage- based inspection system was applied to monitor the condition of cables.
This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of
the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel
cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the
magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to
determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were
compared with thresholds set for objective decision making. In addition, the measured magnetic flux signal was
visualized into a 3D MFL map for convenient cable monitoring. Finally, the results were compared with information on
actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.
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.
This paper presents an interim report on an international collaborative research project between the United States and
Korea that fundamentally addresses the challenges associated with integrating structural health monitoring (SHM)
system components into a comprehensive system for bridges. The objective of the project is to integrate and validate
cutting-edge sensors and SHM methods under development for monitoring the long-term performance and structural
integrity of highway bridges. A variety of new sensor and monitoring technologies have been selected for integration
including wireless sensors, EM stress sensors and piezoelectric active sensors. Using these sensors as building blocks,
the first phase of the study focuses on the design of a comprehensive SHM system that is deployed upon a series of
highway bridges in Korea. With permanently installed SHM systems in place, the second phase of the study provides
open access to the bridges and response data continuously collected as an internal test-bed for SHM. Currently, basic
facilities including Internet lines have been constructed on the test-beds, and the participants carried out tests on bridges
on the test road section owned by the Korea Expressway Corporation (KEC) with their own measurement and
monitoring systems in the local area network environment. The participants were able to access and control their
measurement systems by using Remote Desktop in Windows XP through Internet. Researchers interested in this test-bed
are encouraged to join in the collaborative research.
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.
Proc. SPIE. 6532, Health Monitoring of Structural and Biological Systems 2007
KEYWORDS: Statistical analysis, Aerospace engineering, Sensors, Diagnostics, Nondestructive evaluation, Structural health monitoring, Damage detection, Bridges, Microsoft Foundation Class Library, Temperature metrology
This paper presents an impedance-based structural health monitoring (SHM) technique considering temperature effects.
The temperature variation results in a significant impedance variation, particularly a frequency shift in the impedance,
which may lead to erroneous diagnostic results of real structures such as civil, mechanical, and aerospace structures. A
new damage detection strategy has been proposed based on the correlation coefficient (CC) between the reference
impedance data and a concurrent impedance data with an effective frequency shift which is defined as the shift causing
the maximum correlation. The proposed technique was applied to a lab-sized steel truss bridge member under the
temperature varying environment. It has been found, however, the CC values are still suffering from the significant
fluctuation due to the temperature variation. Therefore, an outlier analysis providing the optimal decision boundary has
been carried out for damage detection. From an experimental study, it has been demonstrated that a narrow cut inflicted
artificially to the steel structure was successfully detected using the proposed SHM strategy.