[HTML][HTML] Improving aircraft performance using machine learning: A review
This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …
[HTML][HTML] Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm
M Martinez-Luengo, A Kolios, L Wang - Renewable and Sustainable …, 2016 - Elsevier
Offshore Wind has become the most profitable renewable energy source due to the
remarkable development it has experienced in Europe over the last decade. In this paper, a …
remarkable development it has experienced in Europe over the last decade. In this paper, a …
[HTML][HTML] On robust regression analysis as a means of exploring environmental and operational conditions for SHM data
In the data-based approach to structural health monitoring (SHM), the absence of data from
damaged structures in many cases forces a dependence on novelty detection as a means of …
damaged structures in many cases forces a dependence on novelty detection as a means of …
Physics-informed machine learning for structural health monitoring
The use of machine learning in structural health monitoring is becoming more common, as
many of the inherent tasks (such as regression and classification) in developing condition …
many of the inherent tasks (such as regression and classification) in developing condition …
Aspects of structural health and condition monitoring of offshore wind turbines
I Antoniadou, N Dervilis… - … of the Royal …, 2015 - royalsocietypublishing.org
Wind power has expanded significantly over the past years, although reliability of wind
turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in …
turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in …
Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives
Structural health monitoring (SHM) has been recognized as a useful tool for safety
management and risk reduction of offshore wind farms. In complex offshore environment …
management and risk reduction of offshore wind farms. In complex offshore environment …
Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection
In most real‐world monitoring scenarios, the lack of measurements from damaged
conditions requires the application of unsupervised approaches, mainly the ones based on …
conditions requires the application of unsupervised approaches, mainly the ones based on …
A spectrum of physics-informed Gaussian processes for regression in engineering
Despite the growing availability of sensing and data in general, we remain unable to fully
characterize many in-service engineering systems and structures from a purely data-driven …
characterize many in-service engineering systems and structures from a purely data-driven …
Automatic kernel selection for gaussian processes regression with approximate bayesian computation and sequential monte carlo
The current work introduces a novel combination of two Bayesian tools, Gaussian Processes
(GPs), and the use of the Approximate Bayesian Computation (ABC) algorithm for kernel …
(GPs), and the use of the Approximate Bayesian Computation (ABC) algorithm for kernel …
A regime-switching cointegration approach for removing environmental and operational variations in structural health monitoring
Cointegration is now extensively used to model the long term common trends among
economic variables in the field of econometrics. Recently, cointegration has been …
economic variables in the field of econometrics. Recently, cointegration has been …