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Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network Journal article
Li, D., Wang, Y., Yan, W., Ren, W.X.. Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network[J]. Structural Health Monitoring, 2021, 20(4), 1563-1582.
Authors:  Li, D.;  Wang, Y.;  Yan, W.;  Ren, W.X.
Favorite | TC[WOS]:68 TC[Scopus]:70  IF:5.7/6.8 | Submit date：2022/08/21
Rail  Crack Monitoring  Acoustic Emission  Classification  Synchrosqueezed Wavelet Transform  Multi-branch Convolutional Neural Network  
Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network Journal article
Dan Li, Yang Wang, Wang Ji Yan, Wei Xin Ren. Acoustic emission wave classification for rail crack monitoring based on synchrosqueezed wavelet transform and multi-branch convolutional neural network[J]. Structural Health Monitoring, 2021, 20(4), 1563-1582.
Authors:  Dan Li;  Yang Wang;  Wang Ji Yan;  Wei Xin Ren
Favorite | TC[WOS]:68 TC[Scopus]:70  IF:5.7/6.8 | Submit date：2021/03/11
Rail  Crack Monitoring  Acoustic Emission  Classification  Synchrosqueezed Wavelet Transform  Multi-branch Convolutional Neural Network  
Deep learning-based crack identification for steel pipelines by extracting features from 3d shadow modeling Journal article
Altabey, Wael A., Noori, Mohammad, Wang, Tianyu, Ghiasi, Ramin, Wu, Zhishen. Deep learning-based crack identification for steel pipelines by extracting features from 3d shadow modeling[J]. Applied Sciences (Switzerland), 2021, 11(13), 6063.
Authors:  Altabey, Wael A.;  Noori, Mohammad;  Wang, Tianyu;  Ghiasi, Ramin;  Wu, Zhishen
Favorite | TC[WOS]:18 TC[Scopus]:28  IF:2.5/2.7 | Submit date：2021/12/08
3d Shadow Modeling  Automatic Crack Identification  Convolutional Neural Network (Cnn)  Deep Learning  Structural Health Monitoring (Shm)  
Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling Journal article
Altabey, W. A., Noori, M., Wang, T., Ghiasi, R.. Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling[J]. Applied Sciences, 2021, 1-21.
Authors:  Altabey, W. A.;  Noori, M.;  Wang, T.;  Ghiasi, R.
Favorite |   IF:2.5/2.7 | Submit date：2022/08/30
Deep Learning  Automatic Crack Identification  Convolutional Neural Network (Cnn)  3d Shadow Modeling  Structural Health Monitoring (Shm)