Now showing 1 - 7 of 7
  • Publication
    Monitoring the Condition of a Bridge using a Traffic Speed Deflectometer Vehicle Travelling at Highway Speed
    The Traffic Speed Deflectometer (TSD) is a vehicle incorporating a set of laser Doppler vibrometers on a straight beam to measure the relative velocity between the beam and the pavement surface. This paper describes a numerical study to see if a TSD could be used to detect damage in a bridge. From this measured velocity it is possible to obtain the curvature of the bridge, from whose analysis, it will be demonstrate that information on damage can be extracted. In this paper a Finite Element model is used to simulate the vehicle crossing a single span bridge, for which deflections and curvatures are calculated. From these numerical simulations, it is possible to predict the change in the curvature signal when the bridge is damaged. The method looks promising and it suggests that this drive-by approach is more sensitive to damage than sensors installed on the bridge itself.
      277
  • Publication
    Damage detection using curvatures obtained from vehicle measurements
    This paper describes a new procedure for bridge damage identification through drive-by monitoring. Instantaneous curvature (IC) is presented as a means to determine a local loss of stiffness in a bridge through measurements collected from a passing instrumented vehicle. Moving reference curvature (MRC) is compared with IC as a damage detection tool. It is assumed that absolute displacements on the bridge can be measured by the vehicle. The bridge is represented by a finite element (FE) model. A Half-car model is used to represent the passing vehicle. Damage is represented as a local loss of stiffness in different parts of the bridge. 1% random noise and no noise environments are considered to evaluate the effectiveness of the method. A generic road surface profile is also assumed. Numerical simulations show that the local damage can be detected using IC if the deflection responses can be measured with sufficient accuracy. Damage quantification can be obtained from MRC.
    Scopus© Citations 21  640
  • Publication
    Damage Detection by Drive-by Monitoring Using the Vertical Displacements of a Bridge
    (CRC Press (Taylor & Francis), 2016-09-07) ; ;
    Drive-by monitoring has received increasing attention in recent years, as it has great potential useful for Structural Health Monitoring (SHM) applications. Although direct instrumentation of civil infrastructures has been demonstrated to be a way of detecting damage, it is also a very expensive method as it requires data acquisition, storage and transmission facilities on each bridge. Drive-by constitutes an alternative that allows the monitoring of a bridge without the necessity of installing sensors on it. In this numerical study, the vertical displacements of the bridge are used for damage detection purposes. The goal of this paper is to describe a model that can reproduce the vertical displacements of the bridge when a simulated vehicle is driving through and show how these displacements change with damage. Vertical displacements are calculated before and after damage, so that the sensitivity of the data to bridge damage can be determined. A finite element (FE) model of a simply supported beam interacting with a moving half car is used in this study. Damage is represented as a loss of stiffness in several parts of the bridge. Vertical displacements are generated at a moving reference for healthy and damaged states, corresponding to vehicle location on the bridge. Two options are explored, the first axle and the second one, as the locations to fix the simulated sensor on the vehicle.
      506Scopus© Citations 5
  • Publication
    Application of Image Processing to the Analysis of Congested Traffic
    (Civil Engineering Research Association of Ireland, 2016-08-30) ; ;
    Traffic congestion has become a significant problem in all developed countries. This is mainly due to the increasing number of vehicles but also to the fact that the infrastructures are usually not designed to take over all this traffic. As a result of this increasing number of vehicles on the roads, bridges are becoming serious strangulation points in the transport system. This issue is more important because most of bridges are either approaching or have surpassed their expected design life and traffic data traditionally collected with inductive loops detectors do not provide information about congested traffic situation. Due to this drawback, it needs a better solution for traffic monitoring. The aim of this paper is to explore the capabilities of using images for applications on transport, especially for traffic monitoring, to extract information about traffic such as gaps between cars, cars and trucks, or trucks. In that sense, a high resolution camera will be used in this work in order to capture aerial images of congested traffic. These images will be processed to distinguish all vehicles as different objects on the road, to identify the type of vehicles (regular cars or trucks) and to measure the length for each vehicle. In order to achieve that result, an algorithm able to detect and count the vehicles on the road as separated objects will be firstly applied, enclosing each object within a rectangle.
      159
  • Publication
    Moving Force Identification as a Bridge Damage Indicator
    (International Society for Structural Health Monitoring of Intelligent Infrastructure, 2016-05) ; ;
    Information on the condition of bridges is primarily obtained through the use of visual inspection methods. These methods are unreliable due to an overdependence on human judgement and also inconsistencies due to human objectivity. A scientific approach is a more suitable alternative. Some authors use changes in the natural frequencies of the bridge to indicate possible damage but these methods aren't suitable for local damage detection. Mode shapes have also been used but are more difficult to infer from measurements. This paper investigates the use of a Moving Force Identification (MFI) algorithm in conjunction with bridge deflection data. MFI back-calculates a vehicles applied axle forces to a bridge. It has been found that damage in a bridge changes the calculated axle forces substantially. These calculated axle force histories are used to infer damage from. The damage indicator used here is based on a linear regression analysis of the axle force histories. It is found that the absolute value of the slope of the linear regression fit increases with damage. Hence, by monitoring this parameter, information on possible bridge damage may be supplied on a vehicle by vehicle basis.
      250
  • Publication
    Drive-by Bridge Damage Detection Using Curvatures in Uncertain Environments
    (Civil Engineering Research Association of Ireland, 2016-08-30) ; ;
    Considerable effort has been dedicated in recent years to the development of bridge damage detection techniques. Recently, drive-by monitoring has become popular as it allows the bridge to be monitored without installing sensors on it. In this work, the Traffic Speed Deflectometer (TSD), which incorporates a set of laser Doppler sensors on a straight beam to obtain the relative velocity between the vehicle and the pavement surface, is modelled to obtain deflections on the bridge as the vehicle drives. From these deflections it is possible to obtain the curvature of the bridge, from which inferences on damage can be made. However, most of the time, the measurements taken by drive-by sensors are subject to a set of uncertainties or noise that can lead the damage detection procedure to either give false positives or to miss damage. For that reason, an analysis is needed in order to determine if these methods can work properly in uncertain or noisy environments. Moreover, as the road surface roughness affects the dynamic interaction between the vehicle and the bridge, this may also have an effect on the damage predictions. Hence, the goal of this paper is to study the sensitivity of curvature measurements to both the presence of environmental noise and the effect of the road surface roughness.
      300
  • Publication
    Instantaneous Curvature in Bridge Damage Detection
    Among all the Structural Health Monitoring (SHM) recent methods found in literature, drive-by monitoring has demonstrated to be promising for damage detection purposes, particularly in bridges. As curvatures can be derived from displacement measurements taken by this method, they can also be used for damage detection, which has already been successfully demonstrated. This paper describes the use of Instantaneous Curvature (IC) for that purpose. Once the absolute displacements of the bridge are measured, damage location and quantification can be obtained through IC when having a moving reference over a bridge. In this paper, a bridge is represented by a finite element model of a Euler-Bernoulli beam. A Half-Car model of a vehicle is used to represent a Traffic Speed Deflectometer (TSD), a drive-by monitoring vehicle. Damage is represented as a loss of stiffness in different parts of the bridge and 1 % measurement noise is added. A generic road profile is also considered. Healthy and damaged states of the bridge are compared in order to validate the method.
      235