Abstract

The main aim of this study is to introduce a two-step method for damage identification in moment frame connections using a support vector machine (SVM) and differential evolution algorithm (DEA). In the first step, the potential location of damage in connections is determined through SVM leading to reducing the dimension of the search space. Then, the accurate location and precise amount of damage in connections are determined in the second step via DEA with a high speed. In order to simulate damage in connections, a moment frame is modeled through semi-rigid beam to column connections and the analytical model is used to randomly generate structures with damaged connections as data. Then, SVM is trained and tested using this data, to facilitate natural frequencies are considered as input data and the characteristics of damage in beam to column connections are considered as output data of the network. Now, the possible location of the damage in connections can be determined using the SVM trained. The accurate location and severity of damage are determined by DEA based on the prediction of SVM in the first step. In order to assess the efficiency of the proposed method, two numerical examples are considered with different damage cases and considering noise. A comparative study is also made to judge the performance of the method with that of a work available in the literature. The outcome shows the high efficiency of the proposed method to identify the location and severity of the damage in moment frame connections.

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