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A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …
service life of civil structures. While successful monitoring provides resolute and staunch …
Towards vibration-based damage detection of civil engineering structures: overview, challenges, and future prospects
In this paper, we delve into the evolving landscape of vibration-based structural damage
detection (SDD) methodologies, emphasizing the pivotal role civil structures play in society's …
detection (SDD) methodologies, emphasizing the pivotal role civil structures play in society's …
Integration of deep learning and Bayesian networks for condition and operation risk monitoring of complex engineering systems
A challenging problem in risk and reliability analysis of Complex Engineering Systems
(CES) is performing and updating risk and reliability assessments on the whole system with …
(CES) is performing and updating risk and reliability assessments on the whole system with …
Structural parameter identification using physics-informed neural networks
XY Guo, SE Fang - Measurement, 2023 - Elsevier
A parameter identification framework has been developed based on physics-informed
neural networks (PINNs). Physical constraints are taken into account during the training …
neural networks (PINNs). Physical constraints are taken into account during the training …
Deep learning for nonlinear seismic responses prediction of subway station
P Huang, Z Chen - Engineering Structures, 2021 - Elsevier
A novel and computationally inexpensive method for predicting the nonlinear seismic
response of subway stations using deep learning approaches is developed to reduce the …
response of subway stations using deep learning approaches is developed to reduce the …
A future with machine learning: review of condition assessment of structures and mechanical systems in nuclear facilities
The nuclear industry is exploring applications of Artificial Intelligence (AI), including
autonomous control and management of reactors and components. A condition assessment …
autonomous control and management of reactors and components. A condition assessment …
Damage detection of structures based on wavelet analysis using improved AlexNet
Deep learning-based approaches have garnered a great deal of interest among different
methods in structural health monitoring (SHM), whose primary objective is to assess …
methods in structural health monitoring (SHM), whose primary objective is to assess …
[HTML][HTML] Towards interpretable deep learning: a feature selection framework for prognostics and health management using deep neural networks
In the last five years, the inclusion of Deep Learning algorithms in prognostics and health
management (PHM) has led to a performance increase in diagnostics, prognostics, and …
management (PHM) has led to a performance increase in diagnostics, prognostics, and …
Structural damage severity classification from time-frequency acceleration data using convolutional neural networks
Structural damage identification involves interpretation of vibration measurements to identify
patterns that are indicative of changes in structural characteristics. Identification of such …
patterns that are indicative of changes in structural characteristics. Identification of such …
Unsupervised structural damage detection technique based on a deep convolutional autoencoder
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 …