Abstract: Damage Detection in Single Tapered Rectangular Cross Section Cantilever Beam using Neural Networks based on Vibration Characteristics
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064

Downloads: 120

Research Paper | Mechanical Engineering | India | Volume 8 Issue 4, April 2019

Damage Detection in Single Tapered Rectangular Cross Section Cantilever Beam using Neural Networks based on Vibration Characteristics

Dr. Challa Jayaramulu

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

Edition: Volume 8 Issue 4, April 2019

Pages: 1572 - 1575

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How to Cite this Article?

Dr. Challa Jayaramulu, "Damage Detection in Single Tapered Rectangular Cross Section Cantilever Beam using Neural Networks based on Vibration Characteristics", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20197404, Volume 8 Issue 4, April 2019, 1572 - 1575

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