Data analysis and detection methods for on-line health monitoring of bridge structures
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2002-06-01
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Abstract:Developing an efficient structural health monitoring (SHM) technique is important for reducing potential hazards posed
to the public by damaged civil structures. The ultimate goal of applying SHM is to real-time detect, localize, and quantify
the accumulated structural damage. Traditionally, damage assessment techniques are primarily based on the observation
of the changes of model parameters, such as modal frequencies and vibration shapes. However, several investigations
have pointed out that this technique could be efficient only if very precise measurements are available or large level of
damage exists. It is obvious that a more robust damage assessment algorithm must be developed. The objective of this
research is to develop a new technique, named matched damage processing (MDP) technique, to perform damage
detection, localization, and severity estimation for bridge structures subjected to traffic loading. The MDP technique
builds upon the concept of matched field processing already developed in the underwater acoustics community. In short,
the MDP technique compares measured responses collected from the physical structure with multiple modeled results
calculated based on various damage locations and severity. The comparison is displayed in a contour or image plot with
damage location and severity as the independent coordinates. The concept, effectiveness and robustness of the MDP
technique are numerically demonstrated via a simple example where a simply supported beam is used to model a bridge
and the traffic loading is modeled as a constant weight moving with constant speed across the bridge. A localized
reduction of structural stiffness is applied to represent the occurrence of damage to the bridge. The mode superposition
technique in conjunction with the finite element method is employed to solve the numerical problem. According to the
numerical results, it is found that the MDP technique is effective and robust to estimate location and severity of structural
deterioration.
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