Artificial neural network based delamination prediction in composite plates using vibration signals
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...
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| Format: | Article |
| Language: | English |
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Gruppo Italiano Frattura
2022-12-01
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| Series: | Fracture and Structural Integrity |
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| Online Access: | https://3.64.71.86/index.php/fis/article/view/3834 |
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| author | T. G. Sreekanth M. Senthilkumar S. Manikanta Reddy |
| author_facet | T. G. Sreekanth M. Senthilkumar S. Manikanta Reddy |
| author_sort | T. G. Sreekanth |
| collection | DOAJ |
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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.
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| format | Article |
| id | doaj-art-891e704f5bac49a18df06916cbd55236 |
| institution | Kabale University |
| issn | 1971-8993 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Gruppo Italiano Frattura |
| record_format | Article |
| series | Fracture and Structural Integrity |
| spelling | doaj-art-891e704f5bac49a18df06916cbd552362025-01-03T00:39:27ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932022-12-011763Artificial neural network based delamination prediction in composite plates using vibration signalsT. G. Sreekanth0M. Senthilkumar1S. Manikanta Reddy2Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India.Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India.Department of Production Engineering, PSG College of Technology, Coimbatore-641004, Tamilnadu, India. 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. https://3.64.71.86/index.php/fis/article/view/3834Health monitoringCompositeGFRPDelaminationVibrationNatural frequency |
| spellingShingle | T. G. Sreekanth M. Senthilkumar S. Manikanta Reddy Artificial neural network based delamination prediction in composite plates using vibration signals Fracture and Structural Integrity Health monitoring Composite GFRP Delamination Vibration Natural frequency |
| title | Artificial neural network based delamination prediction in composite plates using vibration signals |
| title_full | Artificial neural network based delamination prediction in composite plates using vibration signals |
| title_fullStr | Artificial neural network based delamination prediction in composite plates using vibration signals |
| title_full_unstemmed | Artificial neural network based delamination prediction in composite plates using vibration signals |
| title_short | Artificial neural network based delamination prediction in composite plates using vibration signals |
| title_sort | artificial neural network based delamination prediction in composite plates using vibration signals |
| topic | Health monitoring Composite GFRP Delamination Vibration Natural frequency |
| url | https://3.64.71.86/index.php/fis/article/view/3834 |
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