Fracture and Structural Integrity e-ISSN 1971-8993 Open access
Structural Integrity and Safety: Experimental and Numerical Perspectives Vol. 17, No. 63 (2023)

Artificial neural network based delamination prediction in composite plates using vibration signals

Author and affiliation details
  • T. G. Sreekanth Corresponding author Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India. ORCID iD0000-0003-3848-7419 sreekanthtg007@gmail.com
  • M. Senthilkumar Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India. ORCID iD0000-0002-3720-0941
  • S. Manikanta Reddy Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India.
DOI
10.3221/IGF-ESIS.63.04
Pages
37-45
Published
Licence
CC BY 4.0
Published inVol. 17, No. 63 (2023)Go to the issue

Abstract

Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and safety of composite components. The presence of damages such as delaminations on the composites reduces its stiffness and further changes the dynamic behaviour of the structures. As the loss in stiffness leads to changes in the natural frequencies, mode shapes, and other aspects of the structure, vibration analysis may be the ideal technique to employ in this case. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network (ANN) is used to determine the position and area of delaminations in GFRP plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated by experimentation. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates.

Keywords

Article history

  1. ReceivedUntil the next stage: 6 days
  2. Revision requestedUntil the next stage: 6 days
  3. RevisedUntil the next stage: 12 days
  4. AcceptedUntil the next stage: 83 days
  5. Published

How to cite

APA

Sreekanth, T. G., Senthilkumar, M., & Manikanta Reddy, S. (2022). Artificial neural network based delamination prediction in composite plates using vibration signals. Fracture and Structural Integrity, 17(63), 37–45. https://doi.org/10.3221/IGF-ESIS.63.04

IEEE

T. G. Sreekanth, M. Senthilkumar, and S. Manikanta Reddy, “Artificial neural network based delamination prediction in composite plates using vibration signals,” Fracture and Structural Integrity, vol. 17, no. 63, pp. 37–45, 2022, doi: 10.3221/IGF-ESIS.63.04.

MLA

Sreekanth, T. G., et al. “Artificial neural network based delamination prediction in composite plates using vibration signals.” Fracture and Structural Integrity, vol. 17, no. 63, 2022, pp. 37–45. https://doi.org/10.3221/IGF-ESIS.63.04.

Chicago

Sreekanth, T. G., M. Senthilkumar, and S. Manikanta Reddy. 2022. “Artificial neural network based delamination prediction in composite plates using vibration signals.” Fracture and Structural Integrity 17 (63): 37–45. https://doi.org/10.3221/IGF-ESIS.63.04.

Harvard

Sreekanth, T.G., Senthilkumar, M. and Manikanta Reddy, S. (2022) ‘Artificial neural network based delamination prediction in composite plates using vibration signals’, Fracture and Structural Integrity, 17(63), pp. 37–45. doi: 10.3221/IGF-ESIS.63.04.

Vancouver

Sreekanth TG, Senthilkumar M, Manikanta Reddy S. Artificial neural network based delamination prediction in composite plates using vibration signals. Fracture and Structural Integrity. 2022;17(63):37-45. doi:10.3221/IGF-ESIS.63.04

BibTeX

@article{sreekanth2022, author = {Sreekanth, T. G. and Senthilkumar, M. and Manikanta Reddy, S.}, title = {Artificial neural network based delamination prediction in composite plates using vibration signals}, journal = {Fracture and Structural Integrity}, year = {2022}, volume = {17}, number = {63}, pages = {37--45}, doi = {10.3221/IGF-ESIS.63.04}, url = {https://doi.org/10.3221/IGF-ESIS.63.04}, issn = {1971-8993} }

RIS

TY - JOUR AU - Sreekanth, T. G. AU - Senthilkumar, M. AU - Manikanta Reddy, S. TI - Artificial neural network based delamination prediction in composite plates using vibration signals JO - Fracture and Structural Integrity T2 - Fracture and Structural Integrity PY - 2022 DA - 2022/12/21 VL - 17 IS - 63 SP - 37 EP - 45 DO - 10.3221/IGF-ESIS.63.04 UR - https://doi.org/10.3221/IGF-ESIS.63.04 SN - 1971-8993 ER -

Licence

Creative Commons Attribution 4.0 International

May be shared and adapted, provided appropriate credit is given. Copyright © 2022 T. G. Sreekanth, M. Senthilkumar, S. Manikanta Reddy.

Copyright 
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