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View article: A meta-transfer learning prediction method with few-shot data for the remaining useful life of rolling bearing
A meta-transfer learning prediction method with few-shot data for the remaining useful life of rolling bearing Open
Rolling bearings are essential components of rotating machinery. It is crucial to predict and manage the health of rolling bearings. This article proposes a meta transfer learning-based remaining useful life (RUL) prediction approach with …
View article: Intelligent fault diagnosis method of rolling bearing based on multi-source domain fast adversarial network
Intelligent fault diagnosis method of rolling bearing based on multi-source domain fast adversarial network Open
Fault diagnosis of rolling bearings is among the most crucial links in the prognostic and health management of bearings. To solve the problem of single-source domain transfer learning that cannot adapt well to the target domain, a transfer…
View article: A domain adaptation network with feature scale preservation for remaining useful life prediction of rolling bearings under variable operating conditions
A domain adaptation network with feature scale preservation for remaining useful life prediction of rolling bearings under variable operating conditions Open
Transfer learning and domain adaptation (DA) methods have been utilized in bearing prognostic and health management, but most of the current DA methods do not take into account the feature scale change of degraded features when aligning th…
View article: Reliable Fault Diagnosis of Bearings Using an Optimized Stacked Variational Denoising Auto-Encoder
Reliable Fault Diagnosis of Bearings Using an Optimized Stacked Variational Denoising Auto-Encoder Open
Variational auto-encoders (VAE) have recently been successfully applied in the intelligent fault diagnosis of rolling bearings due to its self-learning ability and robustness. However, the hyper-parameters of VAEs depend, to a significant …
View article: A Bearing Fault Diagnosis Method Based on PAVME and MEDE
A Bearing Fault Diagnosis Method Based on PAVME and MEDE Open
When rolling bearings have a local fault, the real bearing vibration signal related to the local fault is characterized by the properties of nonlinear and nonstationary. To extract the useful fault features from the collected nonlinear and…
View article: Application of Generalized Composite Multiscale Lempel–Ziv Complexity in Identifying Wind Turbine Gearbox Faults
Application of Generalized Composite Multiscale Lempel–Ziv Complexity in Identifying Wind Turbine Gearbox Faults Open
Wind turbine gearboxes operate in harsh environments; therefore, the resulting gear vibration signal has characteristics of strong nonlinearity, is non-stationary, and has a low signal-to-noise ratio, which indicates that it is difficult t…
View article: A New Intelligent Weak Fault Recognition Framework for Rotating Machinery
A New Intelligent Weak Fault Recognition Framework for Rotating Machinery Open
The presence of strong background noises makes it a challenging task to detect weak fault characteristics in vibration signals collected from rotating machinery. Thus, a two-stage intelligent weak fault recognition framework, which include…
View article: Finite Time Fault Tolerant Attitude Control-Based Observer for a Rigid Satellite Subject to Thruster Faults
Finite Time Fault Tolerant Attitude Control-Based Observer for a Rigid Satellite Subject to Thruster Faults Open
A rigid satellite fault diagnosis strategy, subject to faults of external disturbances and thruster faults, is developed. In this design, an equivalent idea is introduced to design a sliding mode observer that can detect and identify the f…