Now showing 1 - 10 of 26
  • Publication
    Sensitivity of SHM Sensors to Bridge Stiffness
    Bridges play an important role in transport infrastructure and it is necessary to frequently monitor them. Current vibration-based bridge monitoring methods in which bridges are instrumented using several sensors are sometimes not sensitive enough. For this reason, an assessment of sensitivity of sensors to damage is necessary. In this paper a sensitivity analysis to bridge flexural stiffness (EI) is performed. A discussion between the use of strain or deflections is provided. A relation between deflection and stiffness can be set by theorem of virtual work, expressing the problem as a matrix product. Sensitivity is obtained by deriving the deflection respect to the reciprocal of the stiffness at every analysed location of the bridge. It is found that a good match between the deflection and the bridge stiffness profile can be obtained using noise-free measurements. The accuracy of sensors is evaluated numerically in presence of damage and measurement noise. Field measurements in the United States are also described to identify the potential issues in real conditions.
  • Publication
    Acceleration-based Bridge Scour Monitoring
    This paper comes from a research project focused on the safety assessment of bridges using camera-based technologies. The project is developing methods that transform measured sensor signals and video images into a form that is highly damage-sensitive for bridge safety assessment. It will advance sensor-based structural health monitoring with computer-vision and accelerometer-based techniques, leading to practical applications for bridge damage detection. Many sensor types have been used in test installations, with varying degrees of success. Strain gauges and transducers are well established technologies and sufficiently accurate sensors are available at a reasonable cost. However, strain transducers can only detect damage if it occurs close to the point of measurement and are completely insensitive to scour-induced settlement. Deflection at any point on a bridge is a function of support conditions and the flexural stiffness at all points. As such, it has the potential to provide an indication of damage at any point. Deflection can be difficult to measure and some of the partners in this project are working to develop image analysis techniques to improve the accuracy of camera-based deflection measurement systems. Doppler laser vibrometers measure the derivative of deflection with respect to time, i.e., velocity, but they are expensive and it is impractical to deploy large numbers on smaller bridges. Acceleration is the 2nd derivative of deflection so it is, in theory at least, sensitive to scour damage. Furthermore, accelerometers are widely available and can provide accurate measurements at a reasonable cost. This paper reports on the use of acceleration measurements for bridge scour monitoring. Traffic induced acceleration on a bridge is the result of a range of excitations. The signal is influenced by a number of vehicle-related factors such as speed, inter-axle spacing and tyre and suspension properties. In this project, the portion of the acceleration signal in the region of the bridge first natural frequency is filtered from the raw input in order to amplify the portion of the signal most likely to be influenced by bridge damage. Vehicle/bridge dynamic interaction simulations are used to show the nature of the response, before and after filtering. It is shown that the filtered signal is considerably more sensitive to bridge damage than the original raw signal and has good potential for bridge health monitoring.
  • Publication
    Application of output-only modal method in monitoring of bridges using an instrumented vehicle
    In this paper, application of a well-known output-only modal analysis method called Frequency Domain Decomposition (FDD) method in monitoring of bridge frequency is presented. The obtained modal data can be used efficiently for bridge health monitoring. Three measurement strategies are suggested to collect the acceleration responses from vehicle axle for FDD method in a numerical study. It is shown that using multi vehicles leads to better results in compare to using one vehicle. The efficient effect of ambient excitation to all sides of the bridge is also discussed. In addition, application of FDD method in the case of closeness of vehicle frequency to bridge frequency is investigated. Finally, it is discussed that the FDD method can be an efficient alternative to FFT analysis which is common for analysing the vehicle measurement passing over the bridge.
  • Publication
    On the use of drive-by measurement for indirect bridge monitoring
    (University College Dublin. School of Civil Engineering  , 2016) ;
    Indirect bridge monitoring methods, using the responses measured from vehicles passing over bridges, are under development for about a decade. A major advantage of these methods is that they use sensors mounted on the vehicle – no sensors or data acquisition system needs to be installed on the bridge. Most of the proposed methods are based on the identification of dynamic characteristics of the bridge from responses measured on the vehicle, such as natural frequency, mode shapes and damping. In addition, some of the methods seek to directly detect bridge damage based on the interaction between the vehicle and the bridge. A critical review of indirect methods for bridge monitoring is presented and discussion and recommendations on the challenges to be overcome for successful implementation in practice are provided.A novel Short Time Frequency Domain Decomposition (STFDD) method is proposed to estimate bridge mode shapes from the dynamic response of the vehicle. In Frequency Domain Decomposition (FDD), several segments are defined on the bridge and the measurement is performed using two instrumented axles. Here, the FDD method is employed in a multi-stage procedure applied to the bridge segments in sequence. A rescaling process is used to construct the global mode shape vector. Numerical case studies are investigated using Finite Element (FE) models of vehicle bridge interaction (VBI) to validate the effectiveness and performance of the proposed method. In other indirect bridge identification methods, the road profile may excite the vehicle, making it difficult to detect the bridge modes. This is addressed using two concepts: applying external excitation to the bridge and subtracting signals in the axles of successive trailers towed by the vehicle. The results obtained from the numerical investigation demonstrate that the proposed method can estimate the bridge mode shapes with acceptable accuracy. The sensitivity of the method to added white noise is also investigated.A novel algorithm for bridge damage detection based on the mode shapes estimated from a passing vehicle is also presented. The bridge response at the moving coordinate is measured from an instrumented vehicle with laser vibrometers and accelerometers. A modified version of the Short Time Frequency Domain Decomposition (STFDD) method is applied to the measured responses. The bridge mode shapes are estimated with high resolution as is appropriate for damage detection. A damage index based on mode shape squares (MOSS) is used to detect the presence and location of the damage. A numerical case study of a half-car model passing over a bridge is described which validates the performance of the proposed approach. Several damage scenarios are considered including different locations and severities. It is shown that the presence and location of the damage can be detected with acceptable accuracy when the vehicle is moving very slowly. In addition, the performance of the method using higher vehicle speeds is investigated and shows that the approach works well for speeds up to 8 m/s. The sensitivity of the algorithm to measurement noise is also studied by adding several levels of noise to the responses measured on the vehicle.It is shown theoretically that such a response includes three main components; vehicle frequency, bridge natural frequency and a vehicle speed pseudo-frequency component. The Empirical Mode Decomposition (EMD) method is used to decompose the signal into its main components. A damage detection method is proposed using the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component of the response measured on a passing vehicle. Numerical case studies using Finite Element modelling of Vehicle Bridge Interaction are used to show the performance of the proposed method. It is demonstrated that it can successfully localise the damage location in the absence of road profile. A difference in the acceleration signals of healthy and corresponding damaged structures is used to identify the damage location in the presence of road profile.A truck-trailer system is assumed, equipped with an external excitation at a frequency close to one of the bridge natural frequencies. The excitation makes the bridge response dominant at its natural frequency. The acceleration responses are measured on two following axles of the vehicle. It is shown that the amplitude of the signal includes the bridge mode shape data. The energy of the responses measured on two following axles is obtained using the Hilbert Huang Transform. It is shown that the bridge mode shape can be constructed with high resolution using a rescaling process. The presence of road roughness introduces additional contributions to the response measured on the vehicle, in addition to the bridge response. The concept of subtraction of the responses measured from two identical axles is used to remove the effect of road roughness.
  • Publication
    Railway track monitoring using drive-by measurements
    This paper presents the possibility of detecting considerable changes in track stiffness using the measurements from a laser vibrometer installed on a passing train. A numerical model of a two-dimensional train-track system is implemented in Matlab using the finite element method. The loss of stiffness in the track is modeled by reducing the stiffness of the sub-ballast layer of the track at specified points. The instantaneous velocity of the rail under the train is measured using four laser vibrometers mounted on the train. The simulations show that a change in the sub ballast stiffness of the track can be detected and located from the drive-by measurements.
  • Publication
    Cross entropy weight minimization of a compressive strut
    (Research Publishing Services, 2016-05-19) ; ;
    In this study, a population-based optimization algorithm is used to minimize the weight of a compressive strut. A geometrically nonlinear analysis is carried out to get an accurate measure of the structure's true capacity, allowing for individual member and overall structure (and sub-structure) buckling. To overcome the computational challenge of nonlinear analysis, the study uses a simple definition of the onset of instability and hence the number of iterations is cut to a minimum.
  • Publication
    A New Damage Indicator for Drive-by Monitoring using Instantaneous Curvature
    Drive-by monitoring has enhanced the possibilities for bridge damage detection, with the potential to deliver a bridge rating in the time it takes an instrumented vehicle to pass overhead. This paper outlines the importance of Instantaneous Curvature (IC) as an indicator of local damage. For the IC calculation, bridge deflections are measured from the vehicle before and after the occurrence of damage, so that a comparison between the two situations can be made. Differences in curvature are clearly visible in numerical simulations, especially at the damage location. A Finite Element model of a simply supported bridge subject to a crossing vehicle is modelled dynamically. In this paper, the Curvature Ratio (CR) is proposed as the damage indicator, defined as the ratio of IC in the current bridge to IC in the corresponding healthy bridge. Road profile and random noise in the simulated measurements are considered to represent realistic conditions. Simulations in MATLAB demonstrate that CR is an effective indicator in most of the analysis cases.
  • Publication
    Application of Laser Measurement to the Drive-by Inspection of Bridges
    (National Technical University of Athens (NTUA), 2015-05-27) ;
    This paper introduces the application of laser vibrometer measurements to the drive-by inspection of bridges. Drive-by methods usually process the acceleration response measured from an accelerometer installed on a vehicle passing over a bridge. In this paper, two laser vibrometers and two accelerometers are installed on the vehicle to measure a rela-tive velocity between the bridge and vehicle and the vehicle acceleration. The vehicle velocity is removed from the relative velocity by subtracting the time integration of the vehicle accel-eration. It is shown by subtracting two following bridge spatial velocities at moving coordi-nates, that the spatial velocity of the road roughness can be removed. As a result, the bridge velocity at the moving coordinate is obtained. By applying the FFT to the bridge velocity, the fundamental frequency of the bridge is visible in the spectrum.
  • Publication
    Bridge Scour Detection using Vehicle Acceleration Measurements
    Bridge scour is a serious issue concerning bridge condition and can have adverse consequences if undetected. It is the most common cause of bridge collapse today. One method of assessing the issue is through the use of visual inspections but this has drawback in that often an underwater inspection may have to be carried out. This makes it an expensive solution. Human objectivity leads to inconsistencies in the approach also and this is an issue. A sensor-based approach is a suitable alternative due to these reasons. The use of vehicle acceleration measurements to detect scour is analysed in this paper. The continuous wavelet transform is used to decompose the accelerations into time and frequency information. It is found that the location of the pier under which the scour is present can be identified using this method.
  • Publication
    Identification of bridge mode shapes using a passing vehicle
    (International Society for Structural Health Monitoring of Intelligent Infrastructure, 2015-07-03) ;
    This paper describes the Short Time Frequency Domain Decomposition (STFDD) method for identification of bridge mode shapes using the responses measured in a passing vehicle. Several segments are defined on a bridge and a truck-trailers system is employed to measure the signals. Subtraction of the responses measured from following axles on the truck-trailers is used to remove the effect of road profile. The sensitivity of the STFDD method to sampling time interval and vehicle velocity is investigated using numerical studies. It is shown that selecting an optimum time interval may improve the accuracy of the results obtained. Furthermore, keeping vehicle speed below 4 m/s provides enough data for successful identification of bridge mode shapes.