[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 …
EEG artifact removal—state-of-the-art and guidelines
JA Urigüen, B Garcia-Zapirain - Journal of neural engineering, 2015 - iopscience.iop.org
This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …
the main sources of interference encountered in the electroencephalogram (EEG) …
The role of seasonality in the spread of COVID-19 pandemic
It has been reported that the transmission of COVID-19 can be influenced by the variation of
environmental factors due to the seasonal cycle. However, its underlying mechanism in the …
environmental factors due to the seasonal cycle. However, its underlying mechanism in the …
[HTML][HTML] Monitoring and identifying wind turbine generator bearing faults using deep belief network and EWMA control charts
H Li, J Deng, S Yuan, P Feng… - Frontiers in Energy …, 2021 - frontiersin.org
Wind turbines are widely installed as the new source of cleaner energy production. Dynamic
and random stress imposed on the generator bearing of a wind turbine may lead to …
and random stress imposed on the generator bearing of a wind turbine may lead to …
Abrupt shift to hotter and drier climate over inner East Asia beyond the tipping point
Unprecedented heatwave-drought concurrences in the past two decades have been
reported over inner East Asia. Tree-ring–based reconstructions of heatwaves and soil …
reported over inner East Asia. Tree-ring–based reconstructions of heatwaves and soil …
Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution …
Developing an accurate and robust prediction of long-term average global solar irradiation
plays a crucial role in industries such as renewable energy, agribusiness, and hydrology …
plays a crucial role in industries such as renewable energy, agribusiness, and hydrology …
The increasing rate of global mean sea-level rise during 1993–2014
Global mean sea level (GMSL) has been rising at a faster rate during the satellite altimetry
period (1993–2014) than previous decades, and is expected to accelerate further over the …
period (1993–2014) than previous decades, and is expected to accelerate further over the …
[HTML][HTML] New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms
Abstract Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering
(IF) are largely implemented for representing a signal as superposition of simpler well …
(IF) are largely implemented for representing a signal as superposition of simpler well …
A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform
A Bhattacharyya, RB Pachori - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
A review on empirical mode decomposition in fault diagnosis of rotating machinery
Rotating machinery covers a broad range of mechanical equipment and plays a significant
role in industrial applications. It generally operates under tough working environment and is …
role in industrial applications. It generally operates under tough working environment and is …