Damage Detection of Span Bridge Structures Under Moving Loads Using the Hybrid Enhanced SOS-SA Algorithm

Abstract

To detect structural damage, the static deflections due to a moving load, measured at three different points of the structure, are used with the model updating method. In this method, by minimizing the difference between the responses of the damaged and analytical structures, the location and severity of damage are obtained. A new criterion called ‘deflection influence line indicator’ (DILI) is presented and used as an objective function. Moreover, by integrating the enhanced symbiotic organisms search (ESOS) algorithm and the simulated annealing (SA) algorithm, a new algorithm called the ‘hybrid enhanced symbiotic organisms search-simulated annealing algorithm’ (HESOS-SA) is presented which improves on the original ESOS algorithm. In the proposed algorithm, the global search (exploration) is performed by the ESOS algorithm, whereas the local search (exploitation) is done by the SA algorithm. The original SOS and the proposed HESOS-SA algorithms are used to minimize the DILI criterion. In order to assess the performance of the proposed method for structural damage detection, three benchmark structures, including a simply-supported beam and 25-member and 31-member planar truss problems, with a number of damage scenarios are considered. The numerical results demonstrate that, for noise-free data, both the SOS and HESOS-SA algorithms can correctly detect both the location and severity of damage using the DILI criterion. On the other hand, for noisy data, the HESOS-SA algorithm has a more robust performance in damage detection than the SOS algorithm.