Review of fault detection techniques for predictive maintenance
D Divya, B Marath, MB Santosh Kumar - Journal of Quality in …, 2023 - emerald.com
Purpose This study aims to bring awareness to the developing of fault detection systems
using the data collected from sensor devices/physical devices of various systems for …
using the data collected from sensor devices/physical devices of various systems for …
[HTML][HTML] Overview of normal behavior modeling approaches for SCADA-based wind turbine condition monitoring demonstrated on data from operational wind farms
X Chesterman, T Verstraeten, PJ Daems… - Wind Energy …, 2023 - wes.copernicus.org
Condition monitoring and failure prediction for wind turbines currently comprise a hot
research topic. This follows from the fact that investments in the wind energy sector have …
research topic. This follows from the fact that investments in the wind energy sector have …
Data-driven predictive maintenance of wind turbine based on SCADA data
W Udo, Y Muhammad - IEEE Access, 2021 - ieeexplore.ieee.org
Rystad Energy's analysis shows that installed offshore wind capacity will rise to 27.5 GW in
2026 from 10.5 GW in 2020. This report indicates that increasingly complex maintenance …
2026 from 10.5 GW in 2020. This report indicates that increasingly complex maintenance …
Fleet-based early fault detection of wind turbine gearboxes using physics-informed deep learning based on cyclic spectral coherence
The development of a reliable and automated condition monitoring methodology for the
detection of mechanical failures in rotating machinery has garnered much interest in recent …
detection of mechanical failures in rotating machinery has garnered much interest in recent …
A robust fleet-based anomaly detection framework applied to wind turbine vibration data
Large amounts of unlabeled data are produced from wind turbine condition monitoring
systems to catch their operational status. With this unmanageable amount of data …
systems to catch their operational status. With this unmanageable amount of data …
Early fault diagnosis strategy for WT main bearings based on SCADA data and one-class SVM
To reduce the levelized cost of wind energy, through the reduction in operation and
maintenance costs, it is imperative that the wind turbine downtime is reduced through …
maintenance costs, it is imperative that the wind turbine downtime is reduced through …
On the development of offshore wind turbine technology: an assessment of reliability rates and fault detection methods in a changing market
A Turnbull, C McKinnon, J Carrol, A McDonald - Energies, 2022 - mdpi.com
Offshore wind turbine drive train technology is evolving as developers increase size, aim to
maximise availability and adapt to changing electricity grid requirements. This work first of all …
maximise availability and adapt to changing electricity grid requirements. This work first of all …
Using data from similar systems for data-driven condition diagnosis and prognosis of engineering systems: A review and an outline of future research challenges
M Braig, P Zeiler - IEEE Access, 2022 - ieeexplore.ieee.org
Prognostics and health management (PHM) is an engineering approach dealing with the
diagnosis, prognosis, and management of the health state of engineering systems. Methods …
diagnosis, prognosis, and management of the health state of engineering systems. Methods …
Condition monitoring of wind turbines and extraction of healthy training data using an ensemble of advanced statistical anomaly detection models
X Chesterman, T Verstraeten… - … Conference of the …, 2021 - papers.phmsociety.org
Premature failures caused by excessive wear are responsible for a large fraction of the
maintenance costs of wind turbines. Therefore, it is crucial to be able to identify the formation …
maintenance costs of wind turbines. Therefore, it is crucial to be able to identify the formation …
The detection of generator bearing failures on wind turbines using machine learning based anomaly detection
X Chesterman, T Verstraeten, PJ Daems… - Journal of Physics …, 2022 - iopscience.iop.org
In this research an early warning methodological framework is developed that is able to
detect premature failures due to excessive wear. The methodology follows the data-driven …
detect premature failures due to excessive wear. The methodology follows the data-driven …