[HTML][HTML] Physics-informed machine learning: a comprehensive review on applications in anomaly detection and condition monitoring
Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …
various engineering systems. Traditional methods for condition monitoring rely on physics …
Rotating machinery fault-induced vibration signal modulation effects: A review with mechanisms, extraction methods and applications for diagnosis
Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
and their diagnosis can thus be conducted by extracting fault-induced modulation features …
Digital twin-driven intelligent assessment of gear surface degradation
Gearbox has a compact structure, a stable transmission capability, and a high transmission
efficiency. Thus, it is widely applied as a power transmission system in various applications …
efficiency. Thus, it is widely applied as a power transmission system in various applications …
Physics-Informed Residual Network (PIResNet) for rolling element bearing fault diagnostics
Various deep learning methodologies have recently been developed for machine condition
monitoring recently, and they have achieved impressive success in bearing fault …
monitoring recently, and they have achieved impressive success in bearing fault …
A novel vibration-based prognostic scheme for gear health management in surface wear progression of the intelligent manufacturing system
Gearbox has a compact structure, a stable transmission capability, and high transmission
efficiency. Thus, it is widely applied and used as a critical transmission system in intelligent …
efficiency. Thus, it is widely applied and used as a critical transmission system in intelligent …
Bayesian deep-learning for RUL prediction: An active learning perspective
Deep learning (DL) has been intensively exploited for remaining useful life (RUL) prediction
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
in the recent decade. Although with high precision and flexibility, DL methods need sufficient …
Dynamic vision-based machinery fault diagnosis with cross-modality feature alignment
Intelligent machinery fault diagnosis methods have been popularly and successfully
developed in the past decades, and the vibration acceleration data collected by contact …
developed in the past decades, and the vibration acceleration data collected by contact …
A novel gear fatigue monitoring indicator and its application to remaining useful life prediction for spur gear in intelligent manufacturing systems
With the material degradation of gear over its service lifespan, the gearbox is prone to
fatigue, especially under harsh working environments. The interaction between gear fatigue …
fatigue, especially under harsh working environments. The interaction between gear fatigue …
Deep network-based maximum correlated kurtosis deconvolution: A novel deep deconvolution for bearing fault diagnosis
Deconvolution methods (DMs) which can adaptively design the filter for the feature
extraction is the most effective tool to counteract the effect of the transmission path …
extraction is the most effective tool to counteract the effect of the transmission path …
Modified varying index coefficient autoregression model for representation of the nonstationary vibration from a planetary gearbox
Planetary gearbox fault detection is important in terms of life-threatening failure prevention
and maintenance optimization. This article focuses on the representation of the planetary …
and maintenance optimization. This article focuses on the representation of the planetary …