Effective condition monitoring (CM) of wind turbine (WT) is crucial in detecting potential
faults and developing preventive maintenance strategies. However, the frequent false …

Remaining useful life (RUL) prediction technology is a crucial task in prognostics and health
management (PHM) systems, as it contributes to the enhancement of the reliability of …

Remaining useful life (RUL) predictions are a key enabler for predictive maintenance. Data-
driven approaches, typically based on deep neural networks (DNNs), have shown success …

Prognostic health management (PHM) has become important in many industries as a critical
technology to increase machine stability and operational efficiency. Recently, various …

Aeroengines are the core components of an aircraft; therefore, their health determines flight
safety. Currently, owing to their complex structure and problems associated with their …

With the development of sensing techniques, multisensor long-sequence monitoring signals
are available to provide abundant information from sensory and temporal dimensions. It …

Recently, deep learning-based models such as transformer have achieved significant
performance for industrial remaining useful life (RUL) prediction due to their strong …

Fault diagnosis of power equipment is extremely crucial to the stability of power grid
systems. However, complex operating environments, high costs and limitations of single …

The prediction of the remaining useful life (RUL) is of great significance to ensure the safe
operation of industrial equipment and to reduce the cost of regular preventive maintenance …

The prediction of performance degradation for the aero-engine is crucial to its health
management, but the handling of the dynamic spatiotemporal dependence between …