Now showing 1 - 7 of 7
  • Publication
    The Use of the Forced Frequency of a Bridge Due to a Truck Fleet for Estimating Stiffness Losses at Low Speed
    The influence of traffic loads on the dynamic features of a bridge is an external factor that can hinder the true condition of the structure. This paper aims to effectuate a shift in the way this factor is viewed. If the interaction between vehicle and bridge is modeled using the finite element method, the response is based on mass, stiffness, and damping matrices of a coupled vehicle-bridge system that vary with the location of the load at each point in time. The time-varying forced frequencies of a beam bridge model due to a fleet of 3-axle trucks based on eigenvalue analysis (i.e., derived from the matrices of the coupled system) are compared to those obtained using dynamic transient analysis (i.e., derived from the frequency content of the acceleration response of the beam due to a truck crossing). Truck properties are randomly varied within a realistic range to obtain a pattern for the forced vibration due to a truck fleet traveling at an ideal speed of 1 m/s on a 15 m bridge with a smooth surface, and at 10 m/s on a 30 m bridge. These patterns reveal a trend that allows for locating and quantifying the stiffness loss associated with a crack using only the forced frequency. The implementation of this methodology requires the installation of accelerometers on the bridge, and a nearby weigh-in-motion system to identify the traffic fleet of interest. High requirements for frequency resolution limit the application to bridges located on low speed routes.
    Scopus© Citations 2  70
  • Publication
    Accuracy of instantaneous frequencies predicted by the Hilbert-Huang transform for a bridge subjected to a moving vehicle
    This paper investigates the accuracy of the Hilbert-Huang transform (HHT) in capturing the time-varying frequencies of a short-span bridge traversed by a vehicle travelling at a constant speed. The bridge and vehicle are modelled as a simply supported beam and a quarter-car, respectively. The HHT uses empirical mode decomposition to divide the original signal into mono-component signals, called intrinsic mode functions (IMFs), where the Hilbert transform can extract instantaneous frequencies (IFs). Each IMF is associated with a dominant frequency band, although mode mixing is possible. In order to improve the predicted frequencies, several filters are applied before and after performing the HHT with a threefold purpose: (i) to remove the static component, (ii) to isolate the first mode of vibration, and (iii) to obtain meaningful and denoised IFs. The influences of a localized stiffness loss in the bridge, different vehicle speeds, and three signal-to-noise ratios on the results are discussed.
      140
  • Publication
    Localisation and quantification of stiffness loss based on the forced vibration of a beam traversed by a quarter-car
    This paper proposes a method for locating and quantifying bridge damage based on the time-varying forced frequencies due to moving traffic. The vehicle-bridge coupled system is simplified using a quarter-car model and a simply supported beam. Eigenvalue analysis shows that the eigenfrequencies of the coupled system vary for different vehicle positions. If a local stiffness loss is introduced, the forced frequencies associated with the ‘damage’ scenario will differ from those of a reference ‘healthy’ scenario. The differences between both scenarios depend on the location and severity of damage as well as on the mass and frequency ratios between quarter-car and beam models. In practice, bridge acceleration due to the crossing of a vehicle can be measured and processed using a time-frequency signal processing tool to obtain instantaneous frequencies. Changes in local stiffness are determined from comparing those instantaneous frequencies with the eigenfrequencies based on the same bridge and vehicle configuration.
      142Scopus© Citations 1
  • Publication
    Identifying damage in a bridge by analysing rotation response to a moving load
    This article proposes a bridge damage detection method using direct rotation measurements. Initially, numerical analyses are carried out on a one-dimensional (1D) simply supported beam model loaded with a single moving point load to investigate the sensitivity of rotation as a main parameter for damage identification. As a result of this study, the difference in rotation measurements due to a single moving point load obtained for healthy and damaged states is proposed as a damage indicator. A relatively simple laboratory experiment is conducted on a 3-m long simply supported beam structure to validate the results obtained from the numerical analysis. The case of multi-axle vehicles is investigated through numerical analyses of a 1D bridge model and a theoretical basis for damage detection is presented. Finally, a sophisticated 3D dynamic finite element model of a 20-m long simply supported bridge structure is developed by an independent team of researchers and used to test the robustness of the proposed damage detection methodology in a series of blind tests. Rotations from an extensive range of damage scenarios were provided to the main team who applied their methods without prior knowledge of the extent or location of the damage. Results from the blind test simulations demonstrate that the proposed methodology provides a reasonable indication of the bridge condition for all test scenarios.
    Scopus© Citations 26  327
  • Publication
    Numerical analysis of techniques to extract bridge dynamic features from short records of acceleration
    The use of drones in Structural Health Monitoring (SHM) to charge sensors mounted on a bridge and download their data has gathered interest over the last years. This approach presents the advantage of avoiding the need for long cables running over the bridge or for permanent access to electric power on site. Nonetheless, limitations exist regarding the amount of data that can be transmitted through this method. In contrast to traditional approaches to SHM relying on long records to assess the condition of a structure, the scenario envisioned here deals with short amounts of data. In this paper, specific methodologies for extraction of dynamic features from short data bursts of acceleration signal are tested through numerical simulations. The bridge is modelled as a simply supported finite element beam model that is excited by a series of moving concentrated forces, which represent a random traffic load. Initial conditions are varied allowing for scenarios in which the acceleration record may start once the vehicle is already on the bridge, finish before its exit or combine periods of free and forced vibration. The theoretical acceleration response is obtained for healthy and damage conditions of the bridge, and then corrupted with noise. Focus is placed on how effective these techniques are in overcoming the shortcuts derived from noise and from the short duration of the signal. Therefore, techniques to mitigate common problems such as mode-mixing and edge effects are investigated.
      310
  • Publication
    Impact of short-duration acceleration records on the ability of signal processing techniques to derive accurate bridge frequencies
    This paper envisions a scenario in which unmanned aerial vehicles gather data from low-cost and flexible wireless sensor networks, i.e., accelerometers. However, flight duration, coupled with limited sensor battery time, is a substantial technical limitation. In order to assess the impact of these constraints on bridge monitoring, this paper analyses the extraction of bridge dynamic features from short-duration acceleration records. The short acceleration record is simulated using the theoretical response of a simply supported beam subjected to a moving load. Estimated frequencies are obtained in free vibration and compared with the natural frequencies calculated from formula. Given that short records limit the resolution in the frequency domain, the error in the prediction of frequencies will typically decrease as the duration of the signal increases. Signal processing techniques for extracting dynamic features include the Fast Fourier Transform, Frequency Domain Decomposition, Continuous Wavelet Transform and Hilbert-Huang Transform. This paper carries out an assessment of the accuracy of these signal processing techniques in extracting frequencies as a function of the duration of the measurements. Edge effects and loss of resolution are shown to remain key issues to be addressed when the duration of the signal is too short.
      276
  • Publication
    The use of accelerometers in UAVs for bridge health monitoring
    (Seoul National University, 2019-05-26) ; ;
    Unmanned Aerial Vehicles (UAVs) technology has gained considerable popularity in bridge structural health monitoring for its strengths, such as low cost, safety and high energy efficiency. This paper envisions a scenario in which accelerometers are mounted onto UAVs, which then are able to gather acceleration signals by self-attaching to the bridge. However, battery life is an issue in UAVs with the subsequent limitation in the duration of the measurements. Therefore, this paper carries out a simulation on mode shape extraction from a short data burst by utilising an output only technique, the so-called frequency domain decomposition (FDD). Modal assurance criterion (MAC) is used as a statistical indicator to check differences between the estimated mode shapes and the eigenvectors from finite element analysis. The short acceleration response is generated using a planar vehicle-bridge interaction system where the moving load is modelled as two quarter-cars and the bridge is modelled as a simply supported beam. The impact of signal noise, vehicle speed and signal duration on the accuracy of the estimated mode shapes is investigated. FDD is shown to achieve high values of MAC even for short data bursts. Damping ratio is identified as a significant source of MAC discrepancy in the extraction of mode shapes. The stiffness loss due to a crack is introduced in the beam to evaluate how damage affects the mode shape compared to operational effects. How the MAC values vary with crack location and damage severity is discussed for the first three mode shapes.
      198