[HTML][HTML] A systematic review of data fusion techniques for optimized structural health monitoring
Advancements in structural health monitoring (SHM) techniques have spiked in the past few
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
decades due to the rapid evolution of novel sensing and data transfer technologies. This …
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 …
Unsupervised learning-based damage assessment of full-scale civil structures under long-term and short-term monitoring
MH Daneshvar, H Sarmadi - Engineering Structures, 2022 - Elsevier
Abstract Machine learning has become an influential and useful tool for many civil
engineering applications, particularly structural health monitoring (SHM). For this reason …
engineering applications, particularly structural health monitoring (SHM). For this reason …
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 …
Big data analytics and structural health monitoring: a statistical pattern recognition-based approach
Recent advances in sensor technologies and data acquisition systems opened up the era of
big data in the field of structural health monitoring (SHM). Data-driven methods based on …
big data in the field of structural health monitoring (SHM). Data-driven methods based on …
Non-parametric empirical machine learning for short-term and long-term structural health monitoring
A Entezami, H Shariatmadar… - Structural Health …, 2022 - journals.sagepub.com
Early damage detection is an initial step of structural health monitoring. Thanks to recent
advances in sensing technology, the application of data-driven methods based on the …
advances in sensing technology, the application of data-driven methods based on the …
Early damage assessment in large-scale structures by innovative statistical pattern recognition methods based on time series modeling and novelty detection
Time series analysis and novelty detection are effective and promising methods for data-
driven structural health monitoring (SHM) based on the statistical pattern recognition …
driven structural health monitoring (SHM) based on the statistical pattern recognition …
Online unsupervised detection of structural changes using train–induced dynamic responses
This paper exploits unsupervised data-driven structural health monitoring (SHM) in order to
propose a continuous online procedure for damage detection based on train-induced …
propose a continuous online procedure for damage detection based on train-induced …
Online structural health monitoring by model order reduction and deep learning algorithms
Within a structural health monitoring (SHM) framework, we propose a simulation-based
classification strategy to move towards online damage localization. The procedure combines …
classification strategy to move towards online damage localization. The procedure combines …
Structural health monitoring of civil structures: A diagnostic framework powered by deep metric learning
Recent advances in learning systems and sensor technology have enabled powerful
strategies for autonomous data-driven damage detection in structural systems. This work …
strategies for autonomous data-driven damage detection in structural systems. This work …