Time series prediction stands at the forefront of the fourth industrial revolution (Industry 4.0),
offering a crucial analytical tool for the vast data streams generated by modern industrial …

Many transfer learning methods focus on training models between domains with large
differences. However, the data feature distribution varies greatly in different bearing …

Hydraulic piston pump is known as one of the most critical parts in a typical hydraulic
transmission system. It is imperative to probe into an accurate fault diagnosis method to …

Lithium-ion batteries are a green and environmental energy storage component, which have
become the first choice for energy storage due to their high energy density and good cycling …

Remaining useful life (RUL) prediction based on multimodal sensing data is indispensable
for predictive maintenance of aero-engine under cross-working conditions. Although data …

The accurate probabilistic prediction of remaining useful life (RUL) of bearings plays an
important role in ensuring the safe operation of wind turbine maintenance decision making …

With the advent of industry 4.0, multi-sensors are utilized to monitor the degradation process
of machinery. When machinery operating, multi-sensor signals have potential relation with …

Prognostic health management (PHM) has become a crucial part in building highly
automated systems, whose primary task is to precisely predict the remaining useful life …

Multimodality is a universal characteristic of multi-source monitoring data for rotating
machinery. The correlation fusion of multimodal information is a general law to strengthen …

The current prognostics approaches for a network of assets are centralized and reliant on
the availability of assets' sensors, failures, and anomaly data. To address this, the data from …