The Application Of Bridge Weigh-in-motion System On Slab Bridge With Multiple Longitudinal Sensor Locations

Bridge weigh-in-motion(BWIM)system uses instrumented bridge as a large scale to identify axle weights of moving vehicles across the bridge through continuously collected bridge response.Based on Moses' algorithm,most of the commercial BWIM systems take the field-calibrated influence lines(ILs)as a reference to identify axle weights of moving vehicles.It is significant for ILs representing actual boundary conditions of the existing bridges to improve the accuracy of the identified axle weights in BWIM systems.In order to widen the application range of BWIM technology for further improvement,and modify the relevant algorithm of BWIM system based on field test on a 13m-long slab bridge located in Guilin,Guangxi,China,this paper presents the axle weights identification algorithm in terms of single-row sensors algorithm and the axle weights identification algorithm based on multi-row sensors algorithm to evaluate the accuracy of the algorithms.Specific research contents are as follows:(1)The single-row sensors and multi-row sensors algorithm,which are suitable to slab bridge,have been derived separately in detail,and the similarities and differences between the two algorithms have been analyzed.(2)Based on field tests of the simple supported bridge,the bridge responses have been collected by the multi-row sensors when the calibration vehicles moving across the bridge.(3)In order to analyze field tests of the wide slab bridge,two algorithms in this paper have been programed by using Matlab.(4)Based on dynamic responses of field test on the slab bridge,the FAD signals have been analyzed by using time-frequency processing of continuous wavelet transform technique to identify the vehicle information rapidly and precisely.The test result shows that the efficiency of axle identification can be improved with wavelet transform technique.(5)Applying the measured data based on the BWIM system to the ILs algorithm and the multi-row sensors algorithm,respectively,to calculate the single axle weight and gross weight,and analyzing the vehicle information.The results show that the both algorithms have excellent accuracy.The single-row sensors algorithm can obtain a single approximation axle weight,while the multi-row sensors algorithm provides an instantaneous axle weight and can obtain a load-time curve which reflects the variation process of the axle weight,which is closer to the reality.(6)Compare the vehicle information identified by the two algorithms,it is seriously concluded that the multi-row sensors algorithm has better accuracy than the single-row sensors algorithm,and both of them need to calibrate the actual influence lines from different lanes deviate from each other.