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 …
A survey on fault diagnosis of rotating machinery based on machine learning
With the booming development of modern industrial technology, rotating machinery fault
diagnosis is of great significance to improve the safety, efficiency and sustainable …
diagnosis is of great significance to improve the safety, efficiency and sustainable …
Inter-turn short-circuit faults diagnosis in synchronous reluctance machines, using the Luenberger state observer and current's second-order harmonic
Interturn short-circuit faults are one of the most (if not the most) harmful electrical machine
failures, that if not detected and mitigated at a very incipient stage of development may …
failures, that if not detected and mitigated at a very incipient stage of development may …
Residual-hypergraph convolution network: A model-based and data-driven integrated approach for fault diagnosis in complex equipment
Timely and accurate fault diagnosis plays a critical role in today's smart manufacturing
practices, saving invaluable time and expenditure on maintenance process. To date …
practices, saving invaluable time and expenditure on maintenance process. To date …
Demagnetization fault diagnosis of permanent magnet synchronous motors using magnetic leakage signals
F Huang, X Zhang, G Qin, J **e, J Peng… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In most industrial applications, it is difficult to obtain complete demagnetization fault signals
of all conditions with labels for permanent magnet synchronous motor (PMSM), and motors …
of all conditions with labels for permanent magnet synchronous motor (PMSM), and motors …
[HTML][HTML] Convolutional-neural-network-based multi-signals fault diagnosis of induction motor using single and multi-channels datasets
Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …
Fast algorithms for estimating the disturbance inception time in power systems based on time series of instantaneous values of current and voltage with a high …
M Senyuk, S Beryozkina, P Gubin, A Dmitrieva… - Mathematics, 2022 - mdpi.com
The study examines the development and testing of algorithms for disturbance inception
time estimation in a power system using instantaneous values of current and voltage with a …
time estimation in a power system using instantaneous values of current and voltage with a …
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 …
Integrated s-transform-based learning system for detection of arrhythmic fetus
Measurement of abnormal heartbeat rhythm of a fetus to detect arrhythmia using fetal-
electrocardiogram (f-ECG) signals is one of the most convenient methods, used to quickly …
electrocardiogram (f-ECG) signals is one of the most convenient methods, used to quickly …
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 …