In the field of industrial production, machine failures not only negatively affect productivity
and product quality, but also lead to safety accidents, so it is crucial to accurately diagnose …

Generative adversarial networks (GANs) have recently attracted attention owing to their
impressive ability in generating high-quality and novel synthetic datasets such as signals …

As a key component of the rotating machines, rolling bearings are widely used in
mechanical engineering, aerospace and other fields. The health condition is closely related …

Time-series forecasting is widely studied in the data-driven component-level modeling, fault
diagnosis, and performance prediction of aero-engines. The operational data of aero …

For the application of deep learning (DL) models in the field of remaining useful life (RUL)
prediction and predictive maintenance (PdM) of complex equipment, the insufficient training …

Image resolution is crucial to visual measurement accuracy, but on the one hand, the cost of
increasing the resolution of the acquisition device is prohibitive, and on the other hand, the …

As a novel paradigm in machine learning, deep transfer learning (DTL) can harness the
strengths of deep learning for feature representation, while also capitalizing on the …

Aiming at the problems of low accuracy and long calculation time of remaining useful life
(RUL) prediction of aero-engine by the data-driven method, a method for mining aero …