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Research Paper | Mechanical Engineering | Volume 8 Issue 4, April 2019 | Pages: 1572 - 1575 | India
Damage Detection in Single Tapered Rectangular Cross Section Cantilever Beam using Neural Networks based on Vibration Characteristics
Abstract: This paper proposes the use of Artificial Neural Networks (ANN) for the detection of crack location and crack depth in wind turbine blades. Wind turbine blade is approximated by a laminated composite, cantilever tapered beam with a transverse open surface crack. Experimental results are taken from literature to validate the results obtained from the finite element software ANSYS. The numerical data obtained from (FEM) are then used to train a feed-forward back propagation neural network using Matlab. The simulation results show that the proposed Neural Network can precisely detect the crack location and crack depth.
Keywords: cantilever beam, neural networks, vibration, ANSYS
How to Cite?: Dr. Challa Jayaramulu, "Damage Detection in Single Tapered Rectangular Cross Section Cantilever Beam using Neural Networks based on Vibration Characteristics", Volume 8 Issue 4, April 2019, International Journal of Science and Research (IJSR), Pages: 1572-1575, https://www.ijsr.net/getabstract.php?paperid=ART20197404, DOI: https://dx.doi.org/10.21275/ART20197404