Materials and Energy Research CenterInternational Journal of Engineering1025-2495261220131201Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network1433144472214ENMortezaDardel, Babol Noshirvani university of technologyMohammadRakidehsolid Mechanics, Babol Noshirvani University of TechnologyJournal Article19700101Abstract: In this research, at first, the natural frequencies of a cracked beam are obtained analytically, then, location and depth of a crack in beam is identified by neural network method. The research is applied on a beam with an open crack for three different boundary conditions. For this purpose, at first, the natural frequencies of the cracked beam are obtained analytically, to get the examples for training neural network. Then, inversely, the neural network which has been trained by obtained the natural frequencies came from analytically analysis, is used for obtaining the location and depth of the crack. The effect of numbers of 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 mode numbers of the natural frequencies give rise the prediction accuracy to be increasedhttps://www.ije.ir/article_72214_d96296ab79b2a0f3dbdffb000de283fc.pdf