During the design phase of a bridge, certain characteristics are assumed, such as traffic and wind loading. In reality, however, these characteristics can vary, therefore it is very important that the health of such a structure is monitored to evaluate whether it is holding up to the true loading. Due to the ever-increasing size and cost of these structures, it is vital that any anomalies from the expected deflections are detected as soon as possible, allowing remedial action to be taken, and hence trying to prevent disastrous consequences. The use of a kinematic global positioning system (GPS) now allows subcentimeter accuracy to be achieved at a rate of up to 20 Hz, and at maximum distances from the reference GPS receivers to the bridge receivers of up to 20 km. This makes such a system capable of detecting the deflections of long bridges. In addition, accelerometers have been proven useful for such monitoring, allowing precise readings at rates of up to 1,000 Hz. However, both systems have their limitations. A GPS is limited partly by multipath and cycle slips, relatively low frequency of data, as well as the need to have good satellite coverage, while accelerometers are limited due to the fact that the derivations (velocities, displacements) from the original uncompensated acceleration readings will drift over time. The integration of the two systems, however, results in a hybrid arrangement that helps to eliminate the disadvantages of the two separate units. This paper presents an integrated monitoring system, consisting of Leica CRS1000 series and SR530 dual frequency code/carrier phase GPS receivers and a Kistler triaxial accelerometer. One of the SR530 GPS receivers and the accelerometer are physically integrated, and their data are synchronized. Using spectrum analysis, main natural frequencies of a monitored suspension footbridge are identified from the hybrid system. A simple data processing algorithm is presented, as well as the results from field trials to show the potential applications of such a system.
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