Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019
Structural damage identification has received considerable attention during the past
decades. Although several reviews have been presented, some new developments have …
decades. Although several reviews have been presented, some new developments have …
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 …
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
W Fan, Y Chen, J Li, Y Sun, J Feng, H Hassanin… - Structures, 2021 - Elsevier
Abstract Machine learning is one of the key pillars of industry 4.0 that has enabled rapid
technological advancement through establishing complex connections among …
technological advancement through establishing complex connections among …
Structural health monitoring research under varying temperature condition: A review
Suffering from solar radiation, day–night replacement and seasonal changes, the structure
will produce notable temperature behaviour, which has a vital effect on the long-term …
will produce notable temperature behaviour, which has a vital effect on the long-term …
A feature extraction & selection benchmark for structural health monitoring
T Buckley, B Ghosh, V Pakrashi - Structural Health …, 2023 - journals.sagepub.com
There are a large number of time domain, frequency domain and time-frequency signal
processing methods available for univariate feature extraction. However, there is no …
processing methods available for univariate feature extraction. However, there is no …
An artificial neural network methodology for damage detection: Demonstration on an operating wind turbine blade
This study presents a novel artificial neural network (ANN) based methodology within a
vibration-based structural health monitoring framework for robust damage detection. The …
vibration-based structural health monitoring framework for robust damage detection. The …
Bridge management through digital twin-based anomaly detection systems: A systematic review
Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of
the infrastructural assets are in poor conservation condition as has been recently evidenced …
the infrastructural assets are in poor conservation condition as has been recently evidenced …
Effects of environmental and operational conditions on structural health monitoring and non-destructive testing: A systematic review
The development of Structural Health Monitoring (SHM) and Non-Destructive Testing (NDT)
techniques has rapidly evolved and matured over the past few decades. Advances in sensor …
techniques has rapidly evolved and matured over the past few decades. Advances in sensor …
One-dimensional convolutional neural network-based damage detection in structural joints
Structural health monitoring research traditionally focuses on detecting damage in members
excluding the possibility of weakened joint conditions. Efficient model-based joint damage …
excluding the possibility of weakened joint conditions. Efficient model-based joint damage …