[HTML][HTML] Machine learning methods for wind turbine condition monitoring: A review
This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …
used for condition monitoring in wind turbines (eg blade fault detection or generator …
Structural Health Monitoring using deep learning with optimal finite element model generated data
Abstract Identifying damage through Structural Health Monitoring (SHM) methods is
increasingly attracting attention due to multiple maintenance and failure prevention …
increasingly attracting attention due to multiple maintenance and failure prevention …
A combined finite element and hierarchical Deep learning approach for structural health monitoring: Test on a pin-joint composite truss structure
P Seventekidis, D Giagopoulos - Mechanical Systems and Signal …, 2021 - Elsevier
Abstract Structural Health Monitoring (SHM) is an emerging field of engineering with a wide
range of applications. The most common SHM strategies operate on structural responses …
range of applications. The most common SHM strategies operate on structural responses …
Achieving robust damage mode identification of adhesive composite joints for wind turbine blade using acoustic emission and machine learning
D Xu, PF Liu, ZP Chen, JX Leng, L Jiao - Composite Structures, 2020 - Elsevier
Interest in damage mode classification of composite structures by Acoustic Emission (AE)
inspection technique and clustering analysis by machine learning has been increasingly …
inspection technique and clustering analysis by machine learning has been increasingly …
Condition monitoring framework for damage identification in CFRP rotating shafts using Model-Driven Machine learning techniques
G Karyofyllas, D Giagopoulos - Engineering Failure Analysis, 2024 - Elsevier
Real-time condition monitoring (CM) through vibration measurements is instrumental in
detecting faults and enabling predictive maintenance for mechanical systems. The accuracy …
detecting faults and enabling predictive maintenance for mechanical systems. The accuracy …
Nondestructive monitoring techniques for crack detection and localization in RC elements
M Domaneschi, G Niccolini, G Lacidogna… - Applied Sciences, 2020 - mdpi.com
Featured Application Damage assessment of a reinforced concrete (RC) by means of
different nondestructive testing (NDT) techniques. Joined application of a PZT sensor …
different nondestructive testing (NDT) techniques. Joined application of a PZT sensor …
Vibration-based damage detection using finite element modeling and the metaheuristic particle swarm optimization algorithm
I Zacharakis, D Giagopoulos - Sensors, 2022 - mdpi.com
The continuous development of new materials and larger and/or more complex structures
drives the need for the development of more robust, accurate, and sensitive Structural …
drives the need for the development of more robust, accurate, and sensitive Structural …
Generation of controlled delaminations in composites using symmetrical laser shock configuration
Abstract Structural Health Monitoring (SHM) is defined as the process of implementing a
damage identification strategy for aerospace, civil and mechanical engineering …
damage identification strategy for aerospace, civil and mechanical engineering …
Distributed machine learning in materials that couple sensing, actuation, computation and communication
This paper reviews machine learning applications and approaches to detection,
classification and control of intelligent materials and structures with embedded distributed …
classification and control of intelligent materials and structures with embedded distributed …
Extrapolation of AR models using cubic splines for damage progression evaluation in composite structures
This paper presents the potentiality of the use of extrapolation of a set of Auto-Regressive
(AR) models to inspect a future damage sensitive indices based on changes in one-step …
(AR) models to inspect a future damage sensitive indices based on changes in one-step …