Papers by Dilleswararao Chintala
International Journal of Innovative Research in Science, Engineering and Technology, 2016
In recent years, intense research on the detection of crack using the vibration based techniques ... more In recent years, intense research on the detection of crack using the vibration based techniques has been done and various approaches have been developed by researchers. The work reported in this paper is part of an ongoing research on the experimental investigations of the effects of cracks and damages on the integrity of structures, with a view to detect, quantify, and determine their extents and locations .In the present study, vibration analysis is carried out on a cantilever beam with two open transverse cracks, to study the response characteristics Suitable boundary condition are used to find out natural frequency and mode shapes. The simulations have done with the help of ANSYS14.0 software. A neural network for the cracked structure is trained to approximate the response of the structure by the data set prepared for various crack sizes and locations. Feed-forward multi-layer neural networks trained by backpropagation are used to learn the input (the location and depth of a crack)-output (the structural natural frequencies) relation of the structural system. With this trained neural network minimizing the difference from the measured frequencies and also carried out Multiple Regression Analysis to learn input-output relation in similar fashion. A comparative study is performed to check the crack depth and location effects on natural frequencies for beams of rectangular and I cross section. It is verified from the present analysis that the presence of crack decreases the natural frequency of vibration. The mode shapes also changes considerably due to the presence of crack. The frequency of the cracked cantilever beam decreases with increase in the crack depth for the all modes of vibrations.
In recent years, intense research on the detection of crack using the vibration based techniques ... more In recent years, intense research on the detection of crack using the vibration based techniques has been done and various approaches have been developed by researchers. The work reported in this paper is part of an ongoing research on the experimental investigations of the effects of cracks and damages on the integrity of structures, with a view to detect, quantify, and determine their extents and locations .In the present study, vibration analysis is carried out on a cantilever beam with two open transverse cracks, to study the response characteristics Suitable boundary condition are used to find out natural frequency and mode shapes. The simulations have done with the help of ANSYS14.0 software. A neural network for the cracked structure is trained to approximate the response of the structure by the data set prepared for various crack sizes and locations. Feed-forward multi-layer neural networks trained by back-propagation are used to learn the input (the location and depth of a crack)-output (the structural natural frequencies) relation of the structural system. With this trained neural network minimizing the difference from the measured frequencies and also carried out Multiple Regression Analysis to learn input-output relation in similar fashion. A comparative study is performed to check the crack depth and location effects on natural frequencies for beams of rectangular and I cross section. It is verified from the present analysis that the presence of crack decreases the natural frequency of vibration. The mode shapes also changes considerably due to the presence of crack. The frequency of the cracked cantilever beam decreases with increase in the crack depth for the all modes of vibrations.
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Papers by Dilleswararao Chintala