Identification of Truck Types using Strain Sensors include Co-located Strain Gauges

Abstract

A bridge's performance depends on different factors including superstructure type, support conditions, construction materials, environmental conditions and external loading. Identifying and evaluating the loads applied to a bridge, during its effective life, are necessary for assessing the condition and remaining life of that bridge. Furthermore, the influence of dynamic loading on the structural response of the bridge is important to be considered for the safety of the structure. Although ambient loads can be helpful to assess the changes in bridge condition as monitored over time, applying identified loads allows for a more clear understanding as to how the bridge responds to different types of loads.As a part of the Long Term Bridge Performance (LTBP) program, a bridge located in Perry, Utah was subjected to four sets of high speed, live-load tests. For evaluating the bridge response to different types of loads, these live load tests were conducted with four different truck configurations that traversed the bridge in both right and left lanes. In addition, the different trucks traversed the bridge at three different speeds to make it possible to assess the effect of dynamic response of the bridge. Moreover, these different trucks varied in weight and axle spacing. The data were collected through multiple types of sensors, located on different points and some co-located on same points. The sensors used in this study are strain gauges and the response of the co-located sensors was compared to evaluate the reliability of the results.Two different B-WIM methods were used to calculate the speed of the trucks. These methods include the correlation of signals and the derivative of the strains. The performance of these methods for evaluating the accurate speed was studied. The axle 363 Structures Congress 2013 © ASCE 2013 Structures Congress 2013 Downloaded from ascelibrary.org by New York University on 08/05/15. Copyright ASCE. For personal use only; all rights reserved.distances of the trucks were also calculated through the derivative of the strains. Through these B-WIM algorithms and the long-term monitoring system installed on the bridge, the traffic on the bridge and the bridge dynamic response to the truck loadings can be quantified with very simple and inexpensive calculations.

Vehicle weight identification for a bridge with multi-T-girders based on load transverse distribution coefficient

“…Examples indicated that all vehicles across the bridge were identified with an acceptable accuracy and the statistical distribution of vehicle weight was in good agreement with the actual one. Zolghadri et al (2013) applied the B-WIM system with multiple sensors installed on a single-span prestressed concrete bridge for vehicle weight identification.…”

Non-intrusive schemes for speed and axle identification in bridge-weigh-in-motion systems

“…As for the speed estimation, peak-to-peak approach proposed in WAVE project (O'Brien and Žnidarič 2001) has been widely implemented (Cardini and DeWolf 2009, Brown 2011, Zolghadri et al 2013, Richardson et al 2014. The speed is calculated from the time difference of peaks from the strain signals collected at two longitudinal locations.…”