Shear loading detection of through bolts in bridge structures using a percussion‐based one‐dimensional memory‐augmented convolutional neural network-Reference-Cited by-同舟云学术

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Shear loading detection of through bolts in bridge structures using a percussion‐based one‐dimensional memory‐augmented convolutional neural network

Published:2020-07-21 Issue:3 Volume:36 Page:289-301
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer‐Aided Civil and Infrastructure Engineering

Author:

Wang Furui¹,Song Gangbing¹,Mo Yi‐Lung²

Affiliation:

1. Department of Mechanical Engineering University of Houston Houston TX USA

2. Department of Civil and Environmental Engineering University of Houston Houston TX USA

Funder

China Scholarship Council

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12602

Reference66 articles.

1. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

2. Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals

3. Enhanced probabilistic neural network with local decision circles: A robust classifier

4. Passive and Adaptive Damping Systems for Vibration Mitigation and Increased Fatigue Service Life of a Tied Arch Railway Bridge

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2. Nondestructive detection of fiber content in steel fiber reinforced concrete through percussion method coordinated with a hybrid deep learning network;Journal of Building Engineering;2024-06

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4. Detection and diagnosis of concrete void defect using percussion-based method combined with convolutional neural network;Measurement;2024-05

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