Identification of Vehicle Loads on an Orthotropic Deck Steel Box Beam Bridge Based on Optimal Combined Strain Influence Lines

Abstract

Vehicles are critical living loads to bridge structure; thus, identifying vehicle loads is very important for structural health monitoring and safety evaluations. This paper proposed a load identification method based on an optimal combined strain influence line. Firstly, two types of strain gauges were arranged at the lower edge of a deck to monitor the strain response when vehicles cross the deck. One type of sensor was installed at the lower edge of the deck between U-ribs to detect axle information, including the number of axles, wheelbase, and vehicle speed. The other type of sensor was set on the lower edge of U-ribs to identify the axle’s weight. Secondly, structural responses under the vehicle load with known weights across the bridge was used to identify the strain influence line by using least square method. Because the local mechanical characteristic of the deck was very prominent under the wheel load, the strain influence line was short and susceptible to the transverse position of the vehicle. An index of variation coefficient is proposed as the object function, and an optimal combined strain influence line was developed using a genetic algorithm to decrease the influence of the transverse position of the load. Finally, the unknown vehicle load can be identified based on a calibrated combined strain influence line. A numerical simulation and an experimental test were carried out to validate the effectiveness and anti-noise performance of the proposed method. The identified results showed that the proposed algorithm has good accuracy and anti-noise performance.