Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks
The aim of the following paper is to discuss a newly developed approach for the identification of vibration mode shapes of multilayer composite structures. To overcome the limitations of the approaches based on image analysis (two-dimensional structures, high spatial resolution of mode shapes descri...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Materials |
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| Online Access: | https://www.mdpi.com/1996-1944/14/11/2801 |
| _version_ | 1797532824100667392 |
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| author | Bartosz Miller Leonard Ziemiański |
| author_facet | Bartosz Miller Leonard Ziemiański |
| author_sort | Bartosz Miller |
| collection | DOAJ |
| description | The aim of the following paper is to discuss a newly developed approach for the identification of vibration mode shapes of multilayer composite structures. To overcome the limitations of the approaches based on image analysis (two-dimensional structures, high spatial resolution of mode shapes description), convolutional neural networks (CNNs) are applied to create a three-dimensional mode shapes identification algorithm with a significantly reduced number of mode shape vector coordinates. The CNN-based procedure is accurate, effective, and robust to noisy input data. The appearance of local damage is not an obstacle. The change of the material and the occurrence of local material degradation do not affect the accuracy of the method. Moreover, the application of the proposed identification method allows identifying the material degradation occurrence. |
| first_indexed | 2024-03-10T11:04:49Z |
| format | Article |
| id | doaj.art-d19620369916430a83ec4562c8e66a7e |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-10T11:04:49Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Materials |
| spelling | doaj.art-d19620369916430a83ec4562c8e66a7e2023-11-21T21:14:17ZengMDPI AGMaterials1996-19442021-05-011411280110.3390/ma14112801Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural NetworksBartosz Miller0Leonard Ziemiański1Faculty of Civil and Environmental Engineering and Architecture, Rzeszów University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszów, PolandFaculty of Civil and Environmental Engineering and Architecture, Rzeszów University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszów, PolandThe aim of the following paper is to discuss a newly developed approach for the identification of vibration mode shapes of multilayer composite structures. To overcome the limitations of the approaches based on image analysis (two-dimensional structures, high spatial resolution of mode shapes description), convolutional neural networks (CNNs) are applied to create a three-dimensional mode shapes identification algorithm with a significantly reduced number of mode shape vector coordinates. The CNN-based procedure is accurate, effective, and robust to noisy input data. The appearance of local damage is not an obstacle. The change of the material and the occurrence of local material degradation do not affect the accuracy of the method. Moreover, the application of the proposed identification method allows identifying the material degradation occurrence.https://www.mdpi.com/1996-1944/14/11/2801shelllayered compositesmode shapesidentificationmachine learning |
| spellingShingle | Bartosz Miller Leonard Ziemiański Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks Materials shell layered composites mode shapes identification machine learning |
| title | Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks |
| title_full | Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks |
| title_fullStr | Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks |
| title_full_unstemmed | Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks |
| title_short | Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks |
| title_sort | identification of mode shapes of a composite cylinder using convolutional neural networks |
| topic | shell layered composites mode shapes identification machine learning |
| url | https://www.mdpi.com/1996-1944/14/11/2801 |
| work_keys_str_mv | AT bartoszmiller identificationofmodeshapesofacompositecylinderusingconvolutionalneuralnetworks AT leonardziemianski identificationofmodeshapesofacompositecylinderusingconvolutionalneuralnetworks |