Affiliation(s):
Laboratory of Applied Mechanics (LAM), Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam;
moreAffiliation(s): Laboratory of Applied Mechanics (LAM), Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam; Ho Chi Minh City Department of Transportation, Ho Chi Minh City, Vietnam; CIRTECH Institute, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Vietnam;
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Nhi Ngo-Kieu, Thao Nguyen-Da, Toan Pham-Bao, Tam Nguyen-Nhat, Hung Nguyen-Xuan. Deep learning-based signal processing for evaluating energy dispersal in bridge structures[J]. Journal of Zhejiang University Science A,in press.Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/jzus.A2000414
@article{title="Deep learning-based signal processing for evaluating energy dispersal in bridge structures", author="Nhi Ngo-Kieu, Thao Nguyen-Da, Toan Pham-Bao, Tam Nguyen-Nhat, Hung Nguyen-Xuan", journal="Journal of Zhejiang University Science A", year="in press", publisher="Zhejiang University Press & Springer", doi="https://doi.org/10.1631/jzus.A2000414" }
%0 Journal Article %T Deep learning-based signal processing for evaluating energy dispersal in bridge structures %A Nhi Ngo-Kieu %A Thao Nguyen-Da %A Toan Pham-Bao %A Tam Nguyen-Nhat %A Hung Nguyen-Xuan %J Journal of Zhejiang University SCIENCE A %P 672-680 %@ 1673-565X %D in press %I Zhejiang University Press & Springer doi="https://doi.org/10.1631/jzus.A2000414"
TY - JOUR T1 - Deep learning-based signal processing for evaluating energy dispersal in bridge structures A1 - Nhi Ngo-Kieu A1 - Thao Nguyen-Da A1 - Toan Pham-Bao A1 - Tam Nguyen-Nhat A1 - Hung Nguyen-Xuan J0 - Journal of Zhejiang University Science A SP - 672 EP - 680 %@ 1673-565X Y1 - in press PB - Zhejiang University Press & Springer ER - doi="https://doi.org/10.1631/jzus.A2000414"
Abstract: In this paper, we use deep learning to investigate a loss factor function (LF) for measuring energy dispersal in bridge structures in Ho Chi Minh City, Vietnam. The LF is calculated from the power spectral density (PSD) of random vibration signals to account for the mechanical parameters required for detecting structural changes. The LF is applied to many different types of bridge decks such as a prestressed concrete bridge, precast reinforced concrete bridge, and cable-stayed bridge. In addition, to ensure the new parameters are working effectively for the evaluation, a deep learning-based signal processing platform is used along with a convolutional neural network (CNN) to create the training. The training process helps eliminate interference values and errors. This demonstrates that the LF is sensitive to many different real-life structures while previous parameters are sensitive to only particular structures.
Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
Reference
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