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 delamination prediction is one of the most important aspects in ensuring the integrity and safety of such components. The presence of damages such...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Gruppo Italiano Frattura
2023-01-01
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| Series: | Frattura ed Integrità Strutturale |
| Subjects: | |
| Online Access: | https://www.fracturae.com/index.php/fis/article/view/3834/3725 |
| _version_ | 1797975766655303680 |
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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 |
| description | Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delamination prediction is one of the most important aspects in ensuring the integrity and safety of such components. The presence of damages such as delaminations on the composites reduces its stiffness and 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 for delamination prediction. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network is used to determine the position and area of delaminations in glass fiber-reinforced polymer (GFRP) plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated experimentally. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates. |
| first_indexed | 2024-04-11T04:40:38Z |
| format | Article |
| id | doaj.art-dfc6976aa05d4652ab729b31f6814ab8 |
| institution | Directory Open Access Journal |
| issn | 1971-8993 |
| language | English |
| last_indexed | 2024-04-11T04:40:38Z |
| publishDate | 2023-01-01 |
| publisher | Gruppo Italiano Frattura |
| record_format | Article |
| series | Frattura ed Integrità Strutturale |
| spelling | doaj.art-dfc6976aa05d4652ab729b31f6814ab82022-12-28T07:28:54ZengGruppo Italiano FratturaFrattura ed Integrità Strutturale1971-89932023-01-011763374510.3221/IGF-ESIS.63.0410.3221/IGF-ESIS.63.04Artificial neural network based delamination prediction in composite plates using vibration signalsT. G. SreekanthM. SenthilkumarS. Manikanta ReddyDynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delamination prediction is one of the most important aspects in ensuring the integrity and safety of such components. The presence of damages such as delaminations on the composites reduces its stiffness and 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 for delamination prediction. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network is used to determine the position and area of delaminations in glass fiber-reinforced polymer (GFRP) plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated experimentally. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates.https://www.fracturae.com/index.php/fis/article/view/3834/3725health monitoringcompositegfrpdelaminationvibrationnatural frequencyartificial neural network |
| spellingShingle | T. G. Sreekanth M. Senthilkumar S. Manikanta Reddy Artificial neural network based delamination prediction in composite plates using vibration signals Frattura ed Integrità Strutturale health monitoring composite gfrp delamination vibration natural frequency artificial neural network |
| 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 artificial neural network |
| url | https://www.fracturae.com/index.php/fis/article/view/3834/3725 |
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