Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks
Damage identification of composite structures is a major ongoing challenge for a <i>secure</i> operational life-cycle due to the complex, gradual damage behaviour of composite materials. Especially for composite rotors in aero-engines and wind-turbines, a cost-intensive maintenance servi...
Main Authors: | Veronika Scholz, Peter Winkler, Andreas Hornig, Maik Gude, Angelos Filippatos |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/6/2005 |
Similar Items
-
Automatic Retinal Blood Vessel Segmentation Based on Fully Convolutional Neural Networks
by: Yun Jiang, et al.
Published: (2019-09-01) -
DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation
by: Saleh Baghersalimi, et al.
Published: (2019-07-01) -
Liver Cancer Detection Using Hybridized Fully Convolutional Neural Network Based on Deep Learning Framework
by: Xin Dong, et al.
Published: (2020-01-01) -
Multiple-Model Fully Convolutional Neural Networks for Single Object Tracking on Thermal Infrared Video
by: Mohd Asyraf Zulkifley, et al.
Published: (2018-01-01) -
Design of Fully Analogue Artificial Neural Network with Learning Based on Backpropagation
by: F. Paulu, et al.
Published: (2021-06-01)