Review of fault detection and diagnosis techniques for AC motor drives
MA Gultekin, A Bazzi - Energies, 2023 - mdpi.com
Condition monitoring in electric motor drives is essential for operation continuity. This article
provides a review of fault detection and diagnosis (FDD) methods for electric motor drives. It …
provides a review of fault detection and diagnosis (FDD) methods for electric motor drives. It …
Application of Artificial Intelligence-Based Technique in Electric Motors: A Review
Electric motors find widespread application across various industrial fields. The pursuit of
enhanced comprehensive electric motors performance has consistently drawn significant …
enhanced comprehensive electric motors performance has consistently drawn significant …
SPOSDS: A smart Polycystic Ovary Syndrome diagnostic system using machine learning
Abstract Polycystic Ovary Syndrome (PCOS) is a hormonal disorder that affects a large
percentage of women of reproductive age. PCOS causes imbalanced or delayed menstrual …
percentage of women of reproductive age. PCOS causes imbalanced or delayed menstrual …
Review on prognostics and health management in smart factory: From conventional to deep learning perspectives
At present, the fourth industrial revolution is pushing factories toward an intelligent,
interconnected grid of machinery, communication systems, and computational resources …
interconnected grid of machinery, communication systems, and computational resources …
Accurate sensing of power transformer faults from dissolved gas data using random forest classifier aided by data clustering method
N Haque, A Jamshed, K Chatterjee… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
In this paper, a novel approach for accurate sensing of incipient faults occurring in power
transformers is proposed using dissolved gas analysis (DGA) technique. The Duval …
transformers is proposed using dissolved gas analysis (DGA) technique. The Duval …
Effective random forest-based fault detection and diagnosis for wind energy conversion systems
R Fezai, K Dhibi, M Mansouri, M Trabelsi… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Random Forest (RF) is one of the mostly used machine learning techniques in fault
detection and diagnosis of industrial systems. However, its implementation suffers from …
detection and diagnosis of industrial systems. However, its implementation suffers from …
FaultNet: A deep convolutional neural network for bearing fault classification
The increased presence of advanced sensors on the production floors has led to the
collection of datasets that can provide significant insights into machine health. An important …
collection of datasets that can provide significant insights into machine health. An important …
Accurate wavelet thresholding method for ECG signals
K Yu, L Feng, Y Chen, M Wu, Y Zhang, P Zhu… - Computers in Biology …, 2024 - Elsevier
Current wavelet thresholding methods for cardiogram signals captured by flexible wearable
sensors face a challenge in achieving both accurate thresholding and real-time signal …
sensors face a challenge in achieving both accurate thresholding and real-time signal …
A novel adaptive generalized domain data fusion-driven kernel sparse representation classification method for intelligent bearing fault diagnosis
L Cui, Z Jiang, D Liu, H Wang - Expert Systems with Applications, 2024 - Elsevier
Dictionary learning has gradually attracted attention due to its powerful feature
representation ability. However, the time-shift property of collected signals hinders the …
representation ability. However, the time-shift property of collected signals hinders the …
Multi-Domain Kernel Dictionary Learning Sparse Classification Method for Intelligent Machinery Fault Diagnosis
Z Du, D Liu, L Cui - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Sparse representation classification (SRC) has gradually received attention due to its
powerful feature representation ability. However, the discriminative ability of traditional SRC …
powerful feature representation ability. However, the discriminative ability of traditional SRC …