A systematic review of convolutional neural network-based structural condition assessment techniques
With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …
[HTML][HTML] Data-driven structural health monitoring and damage detection through deep learning: State-of-the-art review
Data-driven methods in structural health monitoring (SHM) is gaining popularity due to
recent technological advancements in sensors, as well as high-speed internet and cloud …
recent technological advancements in sensors, as well as high-speed internet and cloud …
[PDF][PDF] A review on deep learning-based structural health monitoring of civil infrastructures
XW Ye, T Jin, CB Yun - Smart Struct. Syst, 2019 - researchgate.net
In the past two decades, structural health monitoring (SHM) systems have been widely
installed on various civil infrastructures for the tracking of the state of their structural health …
installed on various civil infrastructures for the tracking of the state of their structural health …
Localization and classification of structural damage using deep learning single-channel signal-based measurement
Diligent damage identification is a core thrust of structural health monitoring (SHM).
Vibration-based SHM has recently gained paramount importance. Substantial research …
Vibration-based SHM has recently gained paramount importance. Substantial research …
1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
Structural damage detection has been an interdisciplinary area of interest for various
engineering fields. While the available damage detection methods have been in the process …
engineering fields. While the available damage detection methods have been in the process …
Convolutional neural networks for real-time and wireless damage detection
Structural damage detection methods available for structural health monitoring applications
are based on data preprocessing, feature extraction, and feature classification. The feature …
are based on data preprocessing, feature extraction, and feature classification. The feature …
Data-driven structural health monitoring using feature fusion and hybrid deep learning
HV Dang, H Tran-Ngoc, TV Nguyen… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Smart structural health monitoring (SHM) for large-scale infrastructure is an intriguing
subject for engineering communities thanks to its significant advantages such as timely …
subject for engineering communities thanks to its significant advantages such as timely …
Unsupervised structural damage detection technique based on a deep convolutional autoencoder
Z Rastin, G Ghodrati Amiri, E Darvishan - Shock and Vibration, 2021 - Wiley Online Library
Structural health monitoring (SHM) is a hot research topic with the main purpose of damage
detection in a structure and assessing its health state. The major focus of SHM studies in …
detection in a structure and assessing its health state. The major focus of SHM studies in …
Deep residual network framework for structural health monitoring
Convolutional neural networks have been widely employed for structural health monitoring
and damage identification. The convolutional neural network is currently considered as the …
and damage identification. The convolutional neural network is currently considered as the …
A novel deep learning-based method for damage identification of smart building structures
In the past few years, intelligent structural damage identification algorithms based on
machine learning techniques have been developed and obtained considerable attentions …
machine learning techniques have been developed and obtained considerable attentions …