| Orthotropic steel decks(OSDs),as a common deck system,have already been widely used in numerous bridges cases owing to the its advantages like light weight,high capacity,and convenience in construction.However,due to the fact that the OSD is generally welded through various components and also subjected to overloadings,the deck itself is vulnerable to cracks.The cracks may pose vicious threat to the serviceability and safety of deck system and progressively impair the loading capacity.More seriously,the cost to sustain the OSDs in a reliable state is too huge to afford for the management office.Consequently,it is necessary to monitor the vehicle loads in real time to minimize the demages it brings about.When scaling the dynamic vehhicl loads on the deck,the BWIM(Bridge Weigh-in-motion: BWIM)system has been verified as an efficient tool to identify the vehicles’ velocity and axle loads.And that is the main reason for introducing BWIM into OSD.Typically,when the BWIM is put into OSDs to calculate axle loads,the U-ribs is calibrated.This paper introduced a field test to acquire the dynamic response on the soffit of U-rib to reach the point of axle weight calculation.But,even the same strain responses considered,different algorithm inputs would affect the results.That is,each algorithm would reach a result and the results may differentiate in many ways.Here three algorithms are applied to analyze the corresponding benefits and drawbacks.The paper is arranged as following:(1)Develop a field test plan considering the three algorithms adopted to get the dynamic response on U-ribs.(2)Give detailed description of the three axle weighing algorithms,namely traditional Moses algorithm,Factor-C algorithm and U-rib’s Lateral Influence Line algorithm,and then articulate the corresponding calculation processes.(3)The former two algorithm are compared considering the similarity in calculation theory.The Factor-C utilizes the local-effect U-ribs strain to calculate the axle loads.By comparing the identified axle weights accounting for all the calibrated U-rib strain and corresponding part U-rib strain,the comparison shows that the only the part U-rib strain with prominent response can also identify the axle loads in an acceptable level of accuracy.In addition,the U-rib strain,which includes both global response and local response under concentrated wheel loads,is separated into two components(global component and local component)and the local component strain is then used as reference to identify the moving axle loads.The accuracy level of the identified axle loads is superior to those taking the original U-ribs as reference,which proves the feasibility of the application of the separated local component strain in identifying axle loads.(4)Introduce COST323 into classification of the calculation results to define a class.In terms of COST323,the identified axle loads of two mentioned algorithms are compared and also rated,the comparison demonstrates that the Factor-C algorithm has a promising potential to reach a better level of accuracy than the traditional Moses algorithm in identifying axle loads considering averaged errors and standard deviation.The classification shows that the Factor-C algorithm is superior to Moses and the Criteria reached C(15).To make a further analysis,the main obstacle for circumscribe the applicability of both algorithms is the comparatively large errors in light axle identification.(5)The U-rib’s Lateral Influence Line algorithm is able to identify the lateral location of the axle load.With the lateral locations given,it is connected with the lateral influence line of U-rib.And subsequently,the tantamount strain is calculated to assist the identification of axle loads.The results exhibits that U-rib’s Lateral Influence Line algorithm can efficiently monitor the axle loads and it works better in terms of the identification of rear axles due to its great steadibility.(6)Comparison of the three axle weighing algorithms. |
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