Modal parameter based inverse approach for structural joint damage assessment using unified particle swarm optimization

Joint damage constitutes a significant form of damage in particular, in the beam-to-column connection in a steel frame structure. However, it is identified that except only a few neural network based methods, most of the vibration based damage assessment techniques do not deal with such cases. Again, available ANN based methods are unable to provide a general joint damage assessment method which can cater all types of structure. In present study, a joint damage assessment method is proposed using unified particle swarm optimization method which can be used to determine the amount of joint damages in any frame structures. The joint damage is measured as the ratio of reduction in joint fixity factor at connections. The validity of the developed method is established by conducting few numerical and experimental studies. In order to detect damages in large scale structures, sub-structuring approach is employed. It is found that the present algorithm is able to estimate the amount of joint damages with reasonable accuracy.