Fault diagnosis of rolling bearing is crucial for safety of large rotating machinery. However, in
practical engineering, the fault modes of rolling bearings are usually compound faults and …

Fault detection and diagnosis of gear systems using vibration measurements play an
important role in ensuring their functional reliability and safety. Computational intelligence …

Although data-driven methods have been widely used in planetary gearbox fault diagnosis,
the difficulty and high cost of manual labeling leads to little labeled training data, which limits …

In recent years, artificial intelligence technology has been widely used in fault prediction and
health management (PHM). The machine learning algorithm is widely used in the condition …

Signal measurement and diagnosis of wind turbine gearbox are very important for
equipment maintenance. Generative adversarial networks (GAN) are particularly …

The turbofan engine is a pivotal component of the aircraft. Engine components are
susceptible to degradation over the life of their operation, which affects the reliability and …

Deep learning methods recently have gained growing interests and are extensively applied
in the data-driven bearing fault diagnosis. However, current deep learning methods perform …

The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-
energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data …

Fault diagnosis of rolling bearings becomes an important research subject, where the data-
driven deep learning-based techniques have been extensively exploited. While the state-of …

Gear fault detection and remaining useful life estimation are important tasks for monitoring
the health of rotating machinery. In this study, a new benchmark for endurance gear …