[HTML][HTML] Small data challenges for intelligent prognostics and health management: a review
Prognostics and health management (PHM) is critical for enhancing equipment reliability
and reducing maintenance costs, and research on intelligent PHM has made significant …
and reducing maintenance costs, and research on intelligent PHM has made significant …
A pruned-optimized weighted graph convolutional network for axial flow pump fault diagnosis with hydrophone signals
Due to the spatially dispersed occurrence of faults and the challenges associated with
sensor installation in axial flow pump equipment, an underwater acoustic signal collection …
sensor installation in axial flow pump equipment, an underwater acoustic signal collection …
Enhancing bearing fault diagnosis using motor current signals: A novel approach combining time shifting and CausalConvNets
B Guan, X Bao, H Qiu, D Yang - Measurement, 2024 - Elsevier
In motor drive system, Bearing fault detection through motor current signal (MCS) analysis
has gained recognition for its cost-effectiveness and non-invasive nature. However, two …
has gained recognition for its cost-effectiveness and non-invasive nature. However, two …
Spectral intelligent detection for aflatoxin B1 via contrastive learning based on Siamese network
H Zhu, Y Zhao, Q Gu, L Zhao, R Yang, Z Han - Food Chemistry, 2024 - Elsevier
Aflatoxins, harmful substances found in peanuts, corn, and their derivatives, pose significant
health risks. Addressing this, the presented research introduces an innovative MSGhostDNN …
health risks. Addressing this, the presented research introduces an innovative MSGhostDNN …
An unsupervised pairwise comparison learning approach with adaptive network structure for equipment health quantitative assessment
J Zhao, M Yuan, J Cui, S Dong, S Mei - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Accurate health assessment of large and complex equipment is essential to ensure their
safety, availability, and affordability. Existing machine-learning-based approaches for health …
safety, availability, and affordability. Existing machine-learning-based approaches for health …
Meta-adaptive graph convolutional networks with few samples for the fault diagnosis of rotating machinery
X Yu, Z Zhang, B Tang, M Zhao - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
Rotating machinery is an important component of modern electromechanical systems and its
failure can result in significant economic losses. However, existing deep learning methods …
failure can result in significant economic losses. However, existing deep learning methods …
A weakly supervised pairwise comparison learning approach for bearing health quantitative evaluation and remaining useful life prediction
F Zhao, J Cui, M Yuan, J Zhao - Engineering Computations, 2023 - emerald.com
Purpose The purpose of this paper is to present a weakly supervised learning method to
perform health evaluation and predict the remaining useful life (RUL) of rolling bearings …
perform health evaluation and predict the remaining useful life (RUL) of rolling bearings …
A Novel Cross-Domain Data Augmentation and Bearing Fault Diagnosis Method Based on an Enhanced Generative Model
In actual industrial production, differences in product ion conditions lead to variations in the
collected data distribution. This gives rise to a particular problem: while one set of conditions …
collected data distribution. This gives rise to a particular problem: while one set of conditions …
Photovoltaic Panel Defect Detection via Multi-scale Siamese Convolutional Fusion Network with Information Bottleneck Theory
W Ma, B Chen, B Wang, B Chen - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper presents a solution to the challenges in detecting rare faults in photovoltaic
panels, where sample imbalance and diverse damage types lead to a wide range of failure …
panels, where sample imbalance and diverse damage types lead to a wide range of failure …
A novel semi-supervised learning rolling bearing fault diagnosis method based on SNNGAN
Z Qiu, S Fan, H Liang, Q Li, S Lv - Measurement Science and …, 2024 - iopscience.iop.org
In practical industrial environments, rotating machinery typically operates under normal
conditions. As a result, the signals collected are primarily normal signals. This imbalance in …
conditions. As a result, the signals collected are primarily normal signals. This imbalance in …