Robust fault recognition and correction scheme for induction motors using an effective IoT with deep learning approach
Maintaining electrical machines in good working order and increasing their life expectancy
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment
In recent years, the internet of things (IoT) represents the main core of Industry 4.0 for cyber-
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
physic systems (CPS) in order to improve the industrial environment. Accordingly, the …
Effective fault diagnosis based on wavelet and convolutional attention neural network for induction motors
Induction motors are important equipment in modern industry. However, the occurrence of
fatigue failure following an extended period of operation invariably results in a catastrophic …
fatigue failure following an extended period of operation invariably results in a catastrophic …
Fault diagnosis of rolling element bearing based on symmetric cross entropy of neutrosophic sets
A novel symmetric single-valued neutrosophic cross entropy (SVNCE) measure based upon
a newly developed symmetric measure of fuzzy cross entropy is established and then …
a newly developed symmetric measure of fuzzy cross entropy is established and then …
Harnessing attention mechanisms in a comprehensive deep learning approach for induction motor fault diagnosis using raw electrical signals
Induction motors are widely used in various industrial applications due to their simplicity,
robustness, and high efficiency. In recent years, deep learning approaches have shown …
robustness, and high efficiency. In recent years, deep learning approaches have shown …
Fault diagnosis algorithm for pumping unit based on dual-branch time–frequency fusion
F Zhang, Y Li, D Shan, Y Liu, F Ma… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The collected data of a pumping unit contain environmental noise, which significantly
reduces the precision of fault diagnosis. The previous fault detection approach depends on …
reduces the precision of fault diagnosis. The previous fault detection approach depends on …
Performance of Bearing Ball Defect Classification Based on the Fusion of Selected Statistical Features
Among the existing bearing faults, ball ones are known to be the most difficult to detect and
classify. In this work, we propose a diagnosis methodology for these incipient faults' …
classify. In this work, we propose a diagnosis methodology for these incipient faults' …
A novel customised load adaptive framework for induction motor fault classification utilising MFPT bearing dataset
This research presents a novel Customised Load Adaptive Framework (CLAF) for fault
classification in Induction Motors (IMs), utilising the Machinery Fault Prevention Technology …
classification in Induction Motors (IMs), utilising the Machinery Fault Prevention Technology …
Envelope demodulation method based on SET for fault diagnosis of rolling bearings under variable speed
Z Ma, X Li, S Liu, Y Ge, F Lu - Journal of Advanced Mechanical …, 2020 - jstage.jst.go.jp
Time-frequency analysis can effectively reveal the fault characteristics of rolling bearings
under variable speed conditions. However, the traditional time-frequency analysis method …
under variable speed conditions. However, the traditional time-frequency analysis method …
Diagnosis of multiple faults of an induction motor based on Hilbert envelope analysis
Three phase induction motors are widely used in industrial processes and condition
monitoring of these motors is especially important. Broken rotor bars, eccentricity and …
monitoring of these motors is especially important. Broken rotor bars, eccentricity and …