Now showing 1 - 3 of 3
  • Publication
    Empirical mode decomposition of the acceleration response of a prismatic beam subject to a moving load to identify multiple damage locations
    Empirical Mode Decomposition (EMD) is a technique that converts the measured signal into a number of basic functions known as Intrinsic Mode Functions (IMFs). The EMD-based damage detection algorithm relies on the principle that a sudden loss of stiffness in a structural member will cause a discontinuity in the measured response that can be detected through a distinctive spike in the filtered IMF. Recent studies have shown that applying EMD to the acceleration response, due to the crossing of a constant load over a beam finite element model, can be used to detect a single damaged location. In this paper, the technique is further tested using simulations of a beam with multiple damaged sections. The use of a moving average filter on the acceleration response, prior to applying EMD, is also investigated. A bridge deck is modelled as a series of discretized beam elements where a loss of stiffness is introduced at some random locations. The ability of the EMD algorithm to detect more than one damaged section is analysed for a variety of scenarios including a range of bridge lengths, speeds of the moving load and noise levels. The influence of the number of measurement points and their distance to the damaged locations on the accuracy of the predicted damage is also discussed.
      217
  • Publication
    Empirical mode decomposition of the acceleration response of a prismatic beam subject to a moving load to Identify multiple damage locations
    Empirical Mode Decomposition (EMD) is a technique that converts the measured signal into a number of basic functions known as intrinsic mode functions. The EMD-based damage detection algorithm relies on the principle that a sudden loss of stiffness in a structural member will cause a discontinuity in the measured response that can be detected through a distinctive spike in the filtered intrinsic mode function. Recent studies have shown that applying EMD to the acceleration response, due to the crossing of a constant load over a beam finite element model, can be used to detect a single damaged location. In this paper, the technique is further tested using the response of a discretized finite element beam with multiple damaged sections modeled as localized losses of stiffness. The ability of the algorithm to detect more than one damaged section is analysed for a variety of scenarios including a range of bridge lengths, speeds of the moving load and noise levels. The use of a moving average filter on the acceleration response, prior to applying EMD, is shown to improve the sensitivity to damage. The influence of the number of measurement points and their distance to the damaged sections on the accuracy of the predicted damage is also discussed.
      241Scopus© Citations 38
  • Publication
    Theoretical testing of an empirical mode decomposition damage-detection approach using a spatial vehicle-bridge interaction model
    (Taylor and Francis, 2012-07) ;
    Empirical mode decomposition (EMD) is used to detect and locate damage in a bridge using its acceleration response to the crossing of a vehicle. EMD is a technique that converts the measured signal into a number of basic functions that make up the original signal. These functions are obtained purely from the original signal in a sequential procedure, where lower order basic functions contain a range of high frequency components of the signal and higher order basic functions contain the low frequency components. Damage is identified through a distinctive peak in the decomposed signal resulting from applying EMD. Recent studies have shown the potential of this tool to detect single and multiple damages when using the response of a one-dimensional beam model to the crossing of a constant load. In this paper, the technique is further developed using simulations from a quarter-car vehicle-bridge dynamic interaction finite element model. The vehicle model is composed of mass elements, which represent the tyre and body masses, and stiffness and damping elements, which represent tyre and suspension systems. The bridge deck is modelled using plate elements with typical properties found on site and the road profile is generated stochastically from power spectral density functions based on ISO standard guidelines. Different levels of damage are simulated as localised losses of stiffness at random locations within the bridge and a number of longitudinal and transverse locations are used as observation points. The ability of the EMD algorithm to detect damage is analysed for a variety of scenarios including two vehicle configurations (light and heavy), a range of speeds between 5 and 15 m/s, and smooth and rough road surfaces. The influence of the distance from the simulated acceleration points to the damage locations, on the accuracy of the predicted damage, is also discussed.
      500Scopus© Citations 2