Vibration Analysis of a Beam using Neural Network Technique

Abstract

Using changes in global dynamic characteristics for detection of cracks has been a hot research topic now a days and is a source of attraction for civil, aerospace, and mechanical engineering communities in recent years. Crack in vibrating components causes a change in physical properties of a structure which in turn affects dynamic response characteristics. Therefore we have to study the dynamic response characteristics in order to avoid any catastrophic failures and to follow structural integrity and performance for which the parameters considered are crack depth and its location.
In the present study, vibration analysis is carried out on a cantilever beam with two open transverse cracks, to study the response characteristics. Its natural frequency and mode shapes are determined by applying suitable boundary conditions. The results obtained numerically are compared with the results obtained from the simulation. The simulations have done with the help of ALGOR software.
Then by using Feed-forward, back propagation neural network the relationship between the location and the depth of the crack as input and the structural eigenfrequencies as output are studied.
At the end by performing both the simulation and computational analysis it is proved that the presence of cracks affects the natural frequency and the mode shapes of the structure. The results indicate that the current approach can identify both the location and the extent of damages in the beam.