Fault diagnosis and prognosis (FDP) tries to recognize and locate the faults from the
captured sensory data, and also predict their failures in advance, which can greatly help to …

Remaining useful life (RUL) prediction, known as 'prognostics', has long been recognized as
one of the key technologies in prognostics and health management (PHM) to maintain the …

Interpretability of neural networks aims at the development of models that can give
information to the end-user about its inner workings and/or predictions, while keeping the …

The accurate degradation performance assessment of rolling bearings is very important for
the reliable operation of mechanical equipment. However, most current research is limited to …

Accurate forecasting of time series mitigates the uncertainty of future outlooks and is a great
help in reducing errors in decisions. Despite years of researches, there are still some …

Intelligent fault diagnosis, detection, and prognostics (DDP) for complex equipment
prognostics and health management (PHM) have achieved remarkable breakthroughs …

Detecting bearing faults helps ensure the healthy operation of machinery and prevents
serious accidents. However, fault diagnosis method based on deep learning relies on the …

The condition monitoring of rolling bearings has received much attention in prognostics and
health management. Real-time monitoring of the bearings' degradation provides vital …

To enhance RUL prediction accuracy and uncertainty quantification, numerous methods
have been developed, including model-based, data-driven, and hybrid approaches …

This study focuses on the motor fault diagnosis facing the long-tailed distribution data,
characterized by a multitude of fault types with limited data per category and the healthy …