State of the art in structural health monitoring of offshore and marine structures
This paper deals with state of the art in structural health monitoring (SHM) methods in
offshore and marine structures. Most SHM methods have been developed for onshore …
offshore and marine structures. Most SHM methods have been developed for onshore …
Unsupervised learning methods for data-driven vibration-based structural health monitoring: a review
Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …
topic in the structural health monitoring (SHM) research community during the past decades …
Multiattribute multitask transformer framework for vision‐based structural health monitoring
Using deep learning (DL) to recognize building and infrastructure damage via images is
becoming popular in vision‐based structural health monitoring (SHM). However, many …
becoming popular in vision‐based structural health monitoring (SHM). However, many …
On continuous health monitoring of bridges under serious environmental variability by an innovative multi-task unsupervised learning method
Abstract Design of an automated and continuous framework is of paramount importance to
structural health monitoring (SHM). This study proposes an innovative multi-task …
structural health monitoring (SHM). This study proposes an innovative multi-task …
DF-CDM: Conditional diffusion model with data fusion for structural dynamic response reconstruction
In structural health monitoring (SHM) systems, data loss inevitably occurs and reduces the
applicability of SHM techniques, such as condition assessment and damage identification …
applicability of SHM techniques, such as condition assessment and damage identification …
Large‐scale structural health monitoring using composite recurrent neural networks and grid environments
The demand for resilient and smart structures has been rapidly increasing in recent
decades. With the occurrence of the big data revolution, research on data‐driven structural …
decades. With the occurrence of the big data revolution, research on data‐driven structural …
A locally unsupervised hybrid learning method for removing environmental effects under different measurement periods
Environmental effects induce deceptive variability in unlabeled vibration data for structural
health monitoring (SHM). Although unsupervised learning is an effective solution to this …
health monitoring (SHM). Although unsupervised learning is an effective solution to this …
A data-driven approach to full-field nonlinear stress distribution and failure pattern prediction in composites using deep learning
An image-based deep learning framework is developed to predict nonlinear stress
distribution and failure pattern in microstructural representations of composite materials in …
distribution and failure pattern in microstructural representations of composite materials in …
A literature review: Generative adversarial networks for civil structural health monitoring
Structural Health Monitoring (SHM) of civil structures has been constantly evolving with
novel methods, advancements in data science, and more accessible technology to address …
novel methods, advancements in data science, and more accessible technology to address …
[HTML][HTML] Deep learning-based structural health monitoring
This article provides a comprehensive review of deep learning-based structural health
monitoring (DL-based SHM). It encompasses a broad spectrum of DL theories and …
monitoring (DL-based SHM). It encompasses a broad spectrum of DL theories and …