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A review on the progress, challenges and prospects in the modeling, simulation, control and diagnosis of thermodynamic systems
D Zhou, D Huang - Advanced Engineering Informatics, 2024 - Elsevier
Thermodynamic systems play an inestimable role in engineering applications. With the
rising demands for information and automation in operation and maintenance in …
rising demands for information and automation in operation and maintenance in …
Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring
Y Yuan, J Wei, H Huang, W Jiao, J Wang… - … Applications of Artificial …, 2023 - Elsevier
In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
Triplet attention-enhanced residual tree-inspired decision network: A hierarchical fault diagnosis model for unbalanced bearing datasets
In fault classification tasks, deep neural networks (DNNs) have remarkable recognition
performance. Nevertheless, the classification decision processes of DNNs lack hierarchical …
performance. Nevertheless, the classification decision processes of DNNs lack hierarchical …
Channel attention & temporal attention based temporal convolutional network: A dual attention framework for remaining useful life prediction of the aircraft engines
The health of the aircraft engines is of great concern. And it is a key task to predict the
remaining useful life (RUL) of the aircraft engines accurately. However, there are still …
remaining useful life (RUL) of the aircraft engines accurately. However, there are still …
Recognition and optimisation method of impact deformation patterns based on point cloud and deep clustering: Applied to thin-walled tubes
The recognition and clustering of deformation modes are key to constructing impact
deformation constraints for thin-walled structures. This paper transforms the clustering and …
deformation constraints for thin-walled structures. This paper transforms the clustering and …
An adaptive domain adaptation method for rolling bearings' fault diagnosis fusing deep convolution and self-attention networks
Intelligent fault diagnosis methods based on deep learning have attracted significant
attention in recent years. However, it still faces many challenges, including complex and …
attention in recent years. However, it still faces many challenges, including complex and …
Feature-level SMOTE: Augmenting fault samples in learnable feature space for imbalanced fault diagnosis of gas turbines
A challenge in gas turbine fault diagnosis is that labeled fault samples are relatively rare and
much fewer than normal samples. Conventional data augmentation techniques generate …
much fewer than normal samples. Conventional data augmentation techniques generate …
Fault diagnosis study of hydraulic pump based on improved symplectic geometry reconstruction data enhancement method
Aiming at the problem of poor consistency between the enhanced samples and the original
samples in the current data enhancement methods. In this paper, we propose a data …
samples in the current data enhancement methods. In this paper, we propose a data …
Deep attention SMOTE: Data augmentation with a learnable interpolation factor for imbalanced anomaly detection of gas turbines
Anomaly detection of gas turbines faces the significant challenges of data imbalance and
inter-class overlap. In this paper, we develop a novel data augmentation method, namely …
inter-class overlap. In this paper, we develop a novel data augmentation method, namely …
Digital financial asset price fluctuation forecasting in digital economy era using blockchain information: A reconstructed dynamic-bound Levenberg–Marquardt neural …
Digital financial assets such as cryptocurrency are playing an increasingly crucial role in the
digital economy era. Cryptocurrency is characterized by significant volatility and asset price …
digital economy era. Cryptocurrency is characterized by significant volatility and asset price …