Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network

In this research, at first, natural frequencies of a cracked beam are obtained analytically. also, the location and the depth of a crack in the beam are identified by neural network method, in this study. this research is applied on a beam with an open edge crack for three different boundary conditions. for this purpose, firstly, the natural frequencies of the cracked beam are analytically obtained to get the examples for training the neural network. then, inversely, the trained neural network is used for obtaining the location and depth of the crack. the effect of the numbers of the natural frequencies as input of the network was evaluated on the prediction accuracy. results and measure of errors show that the neural network is a powerful method to determine the location and depth of crack. also, increasing the numbers of the natural frequencies causes the prediction accuracy to be increased.