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solid Mechanics, Babol Noshirvani University of Technology
Abstract
Abstract: 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 increased
Dardel, M., & Rakideh, M. (2013). Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network. International Journal of Engineering, 26(12), 1433-1444.
MLA
Morteza Dardel; Mohammad Rakideh. "Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network". International Journal of Engineering, 26, 12, 2013, 1433-1444.
HARVARD
Dardel, M., Rakideh, M. (2013). 'Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network', International Journal of Engineering, 26(12), pp. 1433-1444.
VANCOUVER
Dardel, M., Rakideh, M. Crack Detection of Timoshenko Beams Using Vibration Behavior and Neural Network. International Journal of Engineering, 2013; 26(12): 1433-1444.
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