Abstract
Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow.
Highlights
As of 2016, there were over 614,387 bridges in the United States, most of which were more than 50 years old, with 9.1% of these bridges being structurally deficient [1]
Among many measures of bridge health, the influence line is popular as it removes the variability due to vehicle configuration [3,4,5,6,7]
Detecting axles is necessary as part of such an structural health monitoring (SHM) system
Summary
As of 2016, there were over 614,387 bridges in the United States, most of which were more than 50 years old, with 9.1% of these bridges being structurally deficient [1]. Early BWIM systems had two axle detectors (pneumatic tubes or tape switches) on the road pavement of each lane of interest [9,23] These detectors had problems with durability and disruption to traffic during installation and replacement [19,24]. To overcome these shortcomings, modern BWIM systems use axle-detection concepts called nothing-on-the-road or free-of-axle detector (FAD) that utilize sensors on the underside of the bridge [25,26,27]. In a FAD BWIM system, signals from two additional strain transducers (namely, FAD sensors) are collected at different positions on the bridge, to record time stamps for axles and to find vehicle configuration, axle spacing and speed. Two field tests are carried out to further demonstrate the validity of the proposed method
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