[HTML][HTML] A review on rapid state of health estimation of lithium-ion batteries in electric vehicles
Lithium-ion battery has presented a rapid growth as the power source of electric vehicles
(EVs). The state of health (SOH) estimation plays an important role in ensuring the safe …
(EVs). The state of health (SOH) estimation plays an important role in ensuring the safe …
Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine
Wind turbines play a crucial role in renewable energy generation systems and are frequently
exposed to challenging operational environments. Monitoring and diagnosing potential …
exposed to challenging operational environments. Monitoring and diagnosing potential …
[HTML][HTML] Recent advances in model-based fault diagnosis for lithium-ion batteries: A comprehensive review
Lithium-ion batteries (LIBs) have found wide applications in a variety of fields such as
electrified transportation, stationary storage and portable electronics devices. A battery …
electrified transportation, stationary storage and portable electronics devices. A battery …
Fault transfer diagnosis of rolling bearings across multiple working conditions via subdomain adaptation and improved vision transformer network
P Liang, Z Yu, B Wang, X Xu, J Tian - Advanced Engineering Informatics, 2023 - Elsevier
Due to often working in the environment of variable speeds and loads, it is an enormous
challenge to achieve high-accuracy fault diagnosis (FD) of rolling bearings (RB) via existing …
challenge to achieve high-accuracy fault diagnosis (FD) of rolling bearings (RB) via existing …
WavCapsNet: An interpretable intelligent compound fault diagnosis method by backward tracking
With significant advantages in feature learning, the deep learning-based compound fault
(CF) diagnosis method has brought many successful applications for industrial equipment; …
(CF) diagnosis method has brought many successful applications for industrial equipment; …
Generalized open-set domain adaptation in mechanical fault diagnosis using multiple metric weighting learning network
The problem of practical open-set domain adaptation diagnosis has gained great attention
considering unobserved fault categories in target domain. However, existing studies assume …
considering unobserved fault categories in target domain. However, existing studies assume …
Vibration-current data fusion and gradient boosting classifier for enhanced stator fault diagnosis in three-phase permanent magnet synchronous motors
Permanent magnet synchronous motors (PMSMs) are widely recognized for their precise
control capabilities, making them indispensable in numerous industrial applications. Yet …
control capabilities, making them indispensable in numerous industrial applications. Yet …
C-ECAFormer: A new lightweight fault diagnosis framework towards heavy noise and small samples
In engineering practice, small-sample fault diagnosis of mechanical equipment towards
heavy noise interference poses great challenges for the existing Transformer based …
heavy noise interference poses great challenges for the existing Transformer based …
Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems
In recent years, significant advancements in deep learning technology have facilitated the
development of intelligent health monitoring approaches for energy systems. However …
development of intelligent health monitoring approaches for energy systems. However …
A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems
With the advances in artificial intelligence, there is a growing expectation of more automatic
and intelligent prognostics and health management (PHM) systems for the real-time …
and intelligent prognostics and health management (PHM) systems for the real-time …