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 …
[HTML][HTML] A review of ultrasonic sensing and machine learning methods to monitor industrial processes
Supervised machine learning techniques are increasingly being combined with ultrasonic
sensor measurements owing to their strong performance. These techniques also offer …
sensor measurements owing to their strong performance. These techniques also offer …
Structural damage detection based on transfer learning strategy using digital twins of bridges
S Teng, X Chen, G Chen, L Cheng - Mechanical Systems and Signal …, 2023 - Elsevier
In this paper, a novel structural damage detection (SDD) method based on the digital twin
(DT) and transfer learning (TL) was proposed. The SDD methods based on the …
(DT) and transfer learning (TL) was proposed. The SDD methods based on the …
Transfer-learning guided Bayesian model updating for damage identification considering modeling uncertainty
Modeling uncertainty or modeling error has been widely recognized as one major challenge
in structural model updating for structural identification and damage detection. It renders …
in structural model updating for structural identification and damage detection. It renders …
Foundations and applicability of transfer learning for structural health monitoring of bridges
The number of bridges worldwide is extensive, making it financially and technically
challenging for the authorities to install a structural health monitoring (SHM) system and …
challenging for the authorities to install a structural health monitoring (SHM) system and …
[HTML][HTML] A population-based SHM methodology for heterogeneous structures: Transferring damage localisation knowledge between different aircraft wings
Population-based structural health monitoring (PBSHM) offers a new viewpoint for structural
health monitoring (SHM), allowing diagnostic information to be shared across populations of …
health monitoring (SHM), allowing diagnostic information to be shared across populations of …
Fusing damage-sensitive features and domain adaptation towards robust damage classification in real buildings
Abstract Structural Health Monitoring (SHM) enables the rapid assessment of structural
integrity in the immediate aftermath of strong ground motions. Data-driven techniques, often …
integrity in the immediate aftermath of strong ground motions. Data-driven techniques, often …
[HTML][HTML] A fuzzy-set-based joint distribution adaptation method for regression and its application to online damage quantification for structural digital twin
Online damage quantification suffers from insufficient labeled data that weakens its
accuracy. In this context, adopting the domain adaptation on historical labeled data from …
accuracy. In this context, adopting the domain adaptation on historical labeled data from …
On statistic alignment for domain adaptation in structural health monitoring
The practical application of structural health monitoring is often limited by the availability of
labelled data. Transfer learning–specifically in the form of domain adaptation (DA)–gives …
labelled data. Transfer learning–specifically in the form of domain adaptation (DA)–gives …
Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning
A population‐level analysis is proposed to address data sparsity when building predictive
models for engineering infrastructure. Utilizing an interpretable hierarchical Bayesian …
models for engineering infrastructure. Utilizing an interpretable hierarchical Bayesian …