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Control technologies of wastewater treatment plants: the state-of-the-art, current challenges, and future directions
Existing pieces of literature on previous studies advocate the research focus by various
researchers to reach the benchmark of energy efficiency of Wastewater Treatment Plants …
researchers to reach the benchmark of energy efficiency of Wastewater Treatment Plants …
[HTML][HTML] Early detection of faults in induction motors—A review
There is an increasing interest in improving energy efficiency and reducing operational costs
of induction motors in the industry. These costs can be significantly reduced, and the …
of induction motors in the industry. These costs can be significantly reduced, and the …
Multi-sensor data fusion for rotating machinery fault detection using improved cyclic spectral covariance matrix and motor current signal analysis
When an abnormal situation occurs in rotating machinery, fault feature information may be
scattered on multiple sensors, and fault feature extraction through a single sensor is not …
scattered on multiple sensors, and fault feature extraction through a single sensor is not …
Incipient fault detection in power distribution system: A time–frequency embedded deep-learning-based approach
Incipient fault detection in power distribution systems is crucial to improve the reliability of
the grid. However, the nonstationary nature and the inadequacy of the training dataset due …
the grid. However, the nonstationary nature and the inadequacy of the training dataset due …
A comprehensive interturn fault severity diagnosis method for permanent magnet synchronous motors based on transformer neural networks
This article proposes a novel deep learning (DL)-based interturn short-circuit fault (ISCF)
severity diagnosis method using the transformer neural network (TNN). The input features …
severity diagnosis method using the transformer neural network (TNN). The input features …
Incipient interturn short-circuit fault diagnosis of permanent magnet synchronous motors based on the data-driven digital twin model
Z Chen, D Liang, S Jia, L Yang… - IEEE journal of emerging …, 2023 - ieeexplore.ieee.org
As the most common fault of permanent magnet synchronous motor (PMSM), interturn short-
circuit fault (ISCF) has great harm and develops rapidly. Once it is not diagnosed in time, it …
circuit fault (ISCF) has great harm and develops rapidly. Once it is not diagnosed in time, it …
Fault diagnosis of blast furnace iron-making process with a novel deep stationary kernel learning support vector machine approach
In the blast furnace iron-making process (BFIP), there still has been a significant push to
maintain a stable process and ensure maximum efficiency. Although some control systems …
maintain a stable process and ensure maximum efficiency. Although some control systems …
Development of deep learning-based cooperative fault diagnosis method for multi-PMSM drive system in 4WID-EVs
A deep learning-based cooperative fault diagnosis method is proposed in this study. The
proposed method aims to improve the reliability of contemporary fault diagnosis methods for …
proposed method aims to improve the reliability of contemporary fault diagnosis methods for …
Noise-boosted convolutional neural network for edge-based motor fault diagnosis with limited samples
Convolutional neural networks (CNNs) have been widely applied to motor fault diagnosis.
However, to obtain high recognition accuracy, massive training data are typically required …
However, to obtain high recognition accuracy, massive training data are typically required …
ANC-Net: A novel multi-scale active noise cancellation network for rotating machinery fault diagnosis based on discrete wavelet transform
Rotating machinery often operates in environments filled with a variety of constantly
changing noise, and its working conditions may also vary. This variability causes changes in …
changing noise, and its working conditions may also vary. This variability causes changes in …