Identification of Dynamic Vehicular Axle Loads: Theory and Simulations

Abstract

This paper presents a new method of identifying dynamic vehicular axle loads by directly using bridge measurements. To demonstrate how the proposed methodology works out, vehicle-bridge coupling equations are first established for numerical simulations. The developed vehicle-bridge coupled system contains only the modal properties of the bridge and the physical parameters of the vehicle. Using the superposition principle and influence surface concept, the dynamic interaction forces (i.e. the dynamic axle loads) can then be identified from the measured bridge responses. A series of simulations are carried out in which the effects of various factors such as bridge inertia force, measurement station, vehicle speed, traveling route, number of vehicles, road surface condition, and noise level have been investigated. The identified results show that the proposed method is able to identify dynamic axle loads with good accuracy, which can serve as a basis for dynamic bridge-weigh-in-motion. This paper also serves as a theoretical base for the companion paper in which the proposed method is applied to identify the dynamic axle loads of a real truck on an existing bridge.

A drive-by inspection system via vehicle moving force identification

“…However it has been considered in only a small proportion of moving force identification problems (Chan et al 1999, Law et al 2004, Pinkaew 2006, Deng and Cai 2010b, Wu and Law 2011. In this paper, the vehicle-bridge interaction is modelled as a coupled system as the solution is given at each time step and no iteration is required in the computational process.…”

“…To provide smoother solutions and a bound to the identified forces, the Tikhonov regularisation method (Tikhonov and Arsenin 1977) is included in the solution (Zhu and Law 1999, 2001a, 2001b, 2002, Nordström 2006, Law et al 2007, Gonzalez et al 2008b, Deng and Cai 2010b. Recently, optimisation techniques have been developed for moving force identification which has led to methods which are based on genetic algorithms ) (whereby interaction forces are calculated after estimating vehicle parameters) and simulated annealing genetic algorithms .…”

Simultaneous identification of bridge structural parameters and vehicle loads

“…However, the accuracy of the WIM systems often depends on the road surface condition and the results are reliable only when the vehicle speed is low and bridge pavement surface is smooth [5]. In fact, the dynamic effects of the moving vehicle cause much larger bridge responses, especially when unfavorable road roughness exists, by increasing the average surface damage two to four times compared to that from the static axle forces [5]. In view of this, it would be beneficial if the dynamic axle forces of the operational traffic vehicles as well as the structural parameters could be identified.…”

“…Weigh-in-motion (WIM) systems [2] have been developed, which measure the bridge strains caused by moving vehicles to estimate the equivalent static axle loads [3,4]. However, the accuracy of the WIM systems often depends on the road surface condition and the results are reliable only when the vehicle speed is low and bridge pavement surface is smooth [5]. In fact, the dynamic effects of the moving vehicle cause much larger bridge responses, especially when unfavorable road roughness exists, by increasing the average surface damage two to four times compared to that from the static axle forces [5].…”

“…In view of this, it would be beneficial if the dynamic axle forces of the operational traffic vehicles as well as the structural parameters could be identified. Such information is of particular importance for the purpose of deck and pavement design, management, maintenance, safety assessment as well as fatigue estimation [5,6].…”