Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data
This paper presents a new methodology–based on cointegration analysis of Supervisory
Control And Data Acquisition (SCADA) data–for condition monitoring and fault diagnosis of …
Control And Data Acquisition (SCADA) data–for condition monitoring and fault diagnosis of …
Seismic assessment of bridges through structural health monitoring: a state-of-the-art review
C Karakostas, G Quaranta, E Chatzi, AC Zülfikar… - Bulletin of Earthquake …, 2024 - Springer
The present work offers a comprehensive overview of methods related to condition
assessment of bridges through Structural Health Monitoring (SHM) procedures, with a …
assessment of bridges through Structural Health Monitoring (SHM) procedures, with a …
Multiobjective-clustering-based optimal heterogeneous sensor placement method for thermo-mechanical load identification
The direct measurement of external loads acting on structures remains a challenge in many
engineering applications. In this context, mechanical load identification has received …
engineering applications. In this context, mechanical load identification has received …
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 …
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 …
Shape sensing and damage identification with iFEM on a composite structure subjected to impact damage and non-trivial boundary conditions
L Colombo, D Oboe, C Sbarufatti, F Cadini… - … Systems and Signal …, 2021 - Elsevier
Abstract The inverse Finite Element Method (iFEM) has recently demonstrated to be a
valuable tool, not only for shape sensing, but also for damage identification in a Structural …
valuable tool, not only for shape sensing, but also for damage identification in a Structural …
Damage detection under environmental and operational effects using cointegration analysis–application to experimental data from a cable-stayed bridge
ES Tome, M Pimentel, J Figueiras - Mechanical Systems and Signal …, 2020 - Elsevier
One of the main challenges that Structural Health Monitoring (SHM) faces when transitioning
from academia to real-world applications is the discernment between structural changes due …
from academia to real-world applications is the discernment between structural changes due …
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 …
A cointegration-based approach for automatic anomalies detection in large-scale structures
In recent years, the development of structural health monitoring (SHM) solutions for the
automatic evaluation of the health state of engineering structures is continuously growing …
automatic evaluation of the health state of engineering structures is continuously growing …
Semi-supervised networks integrated with autoencoder and pseudo-labels propagation for structural condition assessment
Insufficient labeled data of vibration measurement from unknown structural states cast great
obstacle to attempt of extending the superiority of deep learning techniques into their rapid …
obstacle to attempt of extending the superiority of deep learning techniques into their rapid …