Application of artificial intelligence in vibration analysis of beams with unconventional boundary conditions

The vibration of a simply supported beam with rotary springs at either ends is studied. The governing equations of motion are investigated considering the nonlinear effect of stretching. These equations are made non-dimensional and then solved to first order approximation using the two methods of the multiple scales and the mode summation. The first five natural frequencies of the beam for few pairs of the boundary condition parameters are evaluated. A multilayer feed-forward back-propagation artificial neural network is trained using these natural frequencies. The artificial neural network used in this study shows high degree of accuracy for the natural frequency of the beam with general pairs of the boundary condition parameters.