[HTML][HTML] Enhanced vision-transformer integrating with semi-supervised transfer learning for state of health and remaining useful life estimation of lithium-ion batteries
YX Wang, S Zhao, S Wang, K Ou, J Zhang - Energy and AI, 2024 - Elsevier
The state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries are crucial
for health management and diagnosis. However, most data-driven estimation methods …
for health management and diagnosis. However, most data-driven estimation methods …
Review of imbalanced fault diagnosis technology based on generative adversarial networks
H Chen, J Wei, H Huang, Y Yuan… - … of Computational Design …, 2024 - academic.oup.com
In the field of industrial production, machine failures not only negatively affect productivity
and product quality, but also lead to safety accidents, so it is crucial to accurately diagnose …
and product quality, but also lead to safety accidents, so it is crucial to accurately diagnose …
Adaptive-conditional loss and correction module enhanced informer network for long-tailed fault diagnosis of motor
M Huang, C Sheng - Journal of Computational Design and …, 2024 - academic.oup.com
This study focuses on the motor fault diagnosis facing the long-tailed distribution data,
characterized by a multitude of fault types with limited data per category and the healthy …
characterized by a multitude of fault types with limited data per category and the healthy …
A Data Augmentation Method for Lithium‐Ion Battery Capacity Estimation Based on Wassertein Time Generative Adversarial Network
Accurate capacity estimation of lithium‐ion battery packs plays an important role in
determining the battery performance degradation. However, performing comprehensive …
determining the battery performance degradation. However, performing comprehensive …
Photovoltaic Cell Anomaly Detection Enabled by Scale Distribution Alignment Learning and Multi-Scale Linear Attention Framework
The growing prevalence of photovoltaic (PV) systems has intensified the focus on fault
prediction and health management within both academic and industrial realms …
prediction and health management within both academic and industrial realms …
[HTML][HTML] A label-free battery state of health estimation method based on adversarial multi-domain adaptation network and relaxation voltage
The state of health (SOH) estimation of lithium-ion batteries is crucial for the operational
reliability and safety of electric vehicles. However, traditional data-driven methods face …
reliability and safety of electric vehicles. However, traditional data-driven methods face …
Energy-Propagation Graph Neural Networks for Enhanced Out-of-Distribution Fault Analysis in Intelligent Construction Machinery Systems
In intelligent fault diagnosis for construction machinery, robust and precise detection of out-
of-distribution (OOD) data is crucial for enhancing operational efficiency and reducing …
of-distribution (OOD) data is crucial for enhancing operational efficiency and reducing …
Easy Transfer Learning-Based Model-Data-Hybrid-Driven Fault Detection for Battery Inverters
In this letter, a hybrid method of fault detection using data and models, based on easy
knowledge transfer learning, is proposed. The proposed method is applied for multiple …
knowledge transfer learning, is proposed. The proposed method is applied for multiple …
A Meta-Learning Method for Few-Shot Multi-Domain State of Health Estimation of Lithium-ion Batteries
Diverse electrochemical characteristics and complex operational conditions of the lithium-
ion battery cause multi-domain discrepancies in practical applications, which poses huge …
ion battery cause multi-domain discrepancies in practical applications, which poses huge …
Uncertainty‐aware nuclear power turbine vibration fault diagnosis method integrating machine learning and heuristic algorithm
Nuclear power turbine fault diagnosis is an important issue in the field of nuclear power
safety. The numerous state parameters in the operation and maintenance of nuclear power …
safety. The numerous state parameters in the operation and maintenance of nuclear power …