Probabilistic data self-clustering based on semi-parametric extreme value theory for structural health monitoring
Clustering is a popular and useful unsupervised learning method with various algorithms for
applying to many engineering problems. However, some practical and technical issues such …
applying to many engineering problems. However, some practical and technical issues such …
[HTML][HTML] Methodology maps for model-based sensor-data interpretation to support civil-infrastructure management
With increasing urbanization and depleting reserves of raw materials for construction,
sustainable management of existing infrastructure will be an important challenge in this …
sustainable management of existing infrastructure will be an important challenge in this …
Gaussian process models for mitigation of operational variability in the structural health monitoring of wind turbines
LD Avendano-Valencia, EN Chatzi… - Mechanical Systems and …, 2020 - Elsevier
The analysis presented in this work relates to the quantification of the effect of a selected set
of measured Environmental and Operational Parameters (EOPs) on the dynamic properties …
of measured Environmental and Operational Parameters (EOPs) on the dynamic properties …
Damage detection of wind turbine blades by Bayesian multivariate cointegration
Abstract Changes in the vibration responses of wind turbine blades (WTBs) can be used to
detect the presence of damages. However, constantly changing environmental …
detect the presence of damages. However, constantly changing environmental …
[HTML][HTML] A genetic algorithm procedure for the automatic updating of fem based on ambient vibration tests
The dynamic identification of the modal parameters of a structure, in order to gain control of
its functionality under operating conditions, is currently under discussion from a scientific …
its functionality under operating conditions, is currently under discussion from a scientific …
Unsupervised long-term damage detection in an uncontrolled environment through optimal autoencoder
K Yang, S Kim, JB Harley - Mechanical Systems and Signal Processing, 2023 - Elsevier
Unsupervised damage detection in the presence of both regular environmental variations,
such as a daily change in temperature and humidity, and irregular environmental variations …
such as a daily change in temperature and humidity, and irregular environmental variations …
[HTML][HTML] Gaussian process time-series models for structures under operational variability
A wide range of vibrating structures are characterized by variable structural dynamics
resulting from changes in environmental and operational conditions, posing challenges in …
resulting from changes in environmental and operational conditions, posing challenges in …
[HTML][HTML] Modeling and monitoring erosion of the leading edge of wind turbine blades
Leading edge surface erosion is an emerging issue in wind turbine blade reliability, causing
a reduction in power performance, aerodynamic loads imbalance, increased noise …
a reduction in power performance, aerodynamic loads imbalance, increased noise …
Addressing practicalities in multivariate nonlinear regression for mitigating environmental and operational variations
C Roberts, DG Cava… - Structural Health …, 2023 - journals.sagepub.com
A significant problem associated with the implementation of Vibration-Based Structural
Health Monitoring (VSHM) systems originates from the detrimental effects caused by …
Health Monitoring (VSHM) systems originates from the detrimental effects caused by …
[HTML][HTML] Robust mitigation of EOVs using multivariate nonlinear regression within a vibration-based SHM methodology
C Roberts, LD Avendaño-Valencia, DG Cava - Mechanical Systems and …, 2024 - Elsevier
A significant issue that has plagued data-driven Vibration-based Structural Health
Monitoring (VSHM) is the mitigation of Environmental and Operational Variations (EOVs) …
Monitoring (VSHM) is the mitigation of Environmental and Operational Variations (EOVs) …