Damage detection on rectangular laminated composite plates using wavelet based convolutional neural network technique. (15th December 2021)
- Record Type:
- Journal Article
- Title:
- Damage detection on rectangular laminated composite plates using wavelet based convolutional neural network technique. (15th December 2021)
- Main Title:
- Damage detection on rectangular laminated composite plates using wavelet based convolutional neural network technique
- Authors:
- Saadatmorad, Morteza
Jafari-Talookolaei, Ramazan-Ali
Pashaei, Mohammad-Hadi
Khatir, Samir - Abstract:
- Highlights: A novel technique is proposed for damage detection of rectangular composite plates. The proposed technique is based on wavelet transform and convolutional neural network. Trial and error efforts are the significant difficulties of the wavelet technique. The proposed technique eliminates the weakness of wavelet transforms. Abstract: In this study, a novel method called the Wavelet Transform-based Convolutional Neural Network (WT-CNN) technique is proposed for damage detection of rectangular laminated composite plates (RLCPs). In the proposed method, the convolutional neural networks and two-dimensional wavelet transform are combined to detect the location of damages in RLCPs. The finite element model (FEM) of damaged RLCPs is developed to generate two-dimensional signals for feeding in the wavelet transform. In order to form a dataset, five hundred single-damage scenarios are applied on a typical RLCP and detected using optimal mother wavelet functions and vanishing moments. The correlation between the class of signals and their best (optimal) wavelet function is considered as the criterion for the best (optimal) wavelet selection. WT-CNN is trained to detect the location of damages in RLCPs. Results show that the proposed WT-CNN can predict and detect the location of damages in RLCPs with high accuracy and eliminate problems of trial and error simulations for future input signals of damaged RLCPs.
- Is Part Of:
- Composite structures. Volume 278(2021)
- Journal:
- Composite structures
- Issue:
- Volume 278(2021)
- Issue Display:
- Volume 278, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 278
- Issue:
- 2021
- Issue Sort Value:
- 2021-0278-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12-15
- Subjects:
- Rectangular laminated composite -- RLCPs -- Wavelet- Convolutional Neural Network Technique -- WT-CNN -- Damage detection
Composite construction -- Periodicals
Composites -- Périodiques
624.18 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02638223 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compstruct.2021.114656 ↗
- Languages:
- English
- ISSNs:
- 0263-8223
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3364.970000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19604.xml