A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges,and in some extreme cases,it will directly lead to a bridge fai...A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges,and in some extreme cases,it will directly lead to a bridge failure.Bridge weigh-in-motion(BWIM)system as a high performance and cost-effective technology has been extensively used to monitor vehicle speed and weight on highways.However,the dynamic effect and data noise may have an adverse impact on the bridge responses during and immediately following the vehicles pass the bridge.The fast Fourier transform(FFT)method,which can significantly purify the collected structural responses(dynamic strains)received from sensors or transducers,was used in axle counting,detection,and axle weighing technology in this study.To further improve the accuracy of the BWIM system,the field-calibrated influence lines(ILs)of a continuous multi-girder bridge were regarded as a reference to identify the vehicle weight based on the modified Moses algorithm and the least squares method.In situ experimental results indicated that the signals treated with FFT filter were far better than the original ones,the efficiency and the accuracy of axle detection were significantly improved by introducing the FFT method to the BWIM system.Moreover,the lateral load distribution effect on bridges should be considered by using the calculated average ILs of the specific lane individually for vehicle weight calculation of this lane.展开更多
基金This research was supported by the Key Research Program and Development Program of Hunan Province(No.2019SK2172)the National Natural Science Foundation of China(Grant No.51178178)+1 种基金the Science and Technology Foundation of Guangdong Provincial Department of Transportation(2010-02-013)The support from these programs is gratefullyacknowledged.The authors would also like to express their gratitude to the anonymous reviewers for their insightful and constructive comments.
文摘A real-time vehicle monitoring is crucial for effective bridge maintenance and traffic management because overloaded vehicles can cause damage to bridges,and in some extreme cases,it will directly lead to a bridge failure.Bridge weigh-in-motion(BWIM)system as a high performance and cost-effective technology has been extensively used to monitor vehicle speed and weight on highways.However,the dynamic effect and data noise may have an adverse impact on the bridge responses during and immediately following the vehicles pass the bridge.The fast Fourier transform(FFT)method,which can significantly purify the collected structural responses(dynamic strains)received from sensors or transducers,was used in axle counting,detection,and axle weighing technology in this study.To further improve the accuracy of the BWIM system,the field-calibrated influence lines(ILs)of a continuous multi-girder bridge were regarded as a reference to identify the vehicle weight based on the modified Moses algorithm and the least squares method.In situ experimental results indicated that the signals treated with FFT filter were far better than the original ones,the efficiency and the accuracy of axle detection were significantly improved by introducing the FFT method to the BWIM system.Moreover,the lateral load distribution effect on bridges should be considered by using the calculated average ILs of the specific lane individually for vehicle weight calculation of this lane.
