The accuracy of fault diagnosis is an important indicator to ensure the reliability of key
equipment systems. Ensemble learning integrates different weak learning methods to obtain …

Rotating machinery fault can cause accidents like loss of flow or turbine trip that seriously
threaten the operation safety of nuclear power plants (NPPs). Artificial intelligence …

Fault diagnosis (FD) of rotating machines is critical to the safety and economic operation of
nuclear power plants (NPPs). Gated Recurrent Unit (GRU) is a gating mechanism in …

Deep learning methods with powerful automatic feature extraction and end-to-end modeling
capabilities can build fault diagnosis models based on raw data without relying on manual …

This work presents a peri-ultrasound theory based on ordinary state-based peridynamics for
modeling elastic waves propagating in three-dimensional (3-D) plate structures and …

Fault diagnosis techniques can detect abnormal states of equipment or systems, give
warning information timely, help to optimize the maintenance schedule, reduce unplanned …

Rotating machinery is widely applied in important equipment of nuclear power plants
(NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating …

Channel structure plays an important role on the performance of proton exchange
membrane fuel cell (PEMFC). In this study, the channel geometry of a PEMFC is optimized …

Rotating machinery is a key component of nuclear power plants (NPPs). The integrity of
rotating machine is related to the safety and economy of the entire NPPs. In order to achieve …

Vibration analysis plays a crucial role in fault and abnormality diagnosis in various
mechanical systems. However, efficient vibration signal processing is required for valuable …