This paper presents an up-to-date review of data-driven condition monitoring of industrial
equipment with the focus on three commonly used equipment: motors, pumps, and bearings …

To implement Prognostics Health Management (PHM) for hydraulic pumps, it is very
important to study the faults of hydraulic pumps to ensure the stability and reliability of the …

Here, a novel hybrid method of intelligent fault identification within complex mechanical
systems was proposed using parallel-factor (PARAFAC) theory and adaptive particle swarm …

Intelligent fault diagnosis (IFD) has been a widely concerned topic in the field of prognostics
and health management. Existing machinery IFD approaches are generally developed …

This work aims to investigate some machinery conditions viz.(healthy, imbalance,
misalignment, gear fault, inner bearing fault, outer bearing fault, and ball bearing fault). The …

The existing intelligent monitoring methods are hard to apply directly to hydraulic machinery
due to fault data collection difficulties and the uncertainty of fault occurrence. To monitor the …

Background Pelton wheel works on Newton's law which converts the kinetic energy of fluid
into mechanical energy. Bearing, nozzle, servomotor and buckets are the main components …

Accurately diagnosing offshore wind turbine bearing faults in noisy environment has long
been a challenge for engineers. This necessitates enhancing diagnostic accuracy while …

This comprehensive review explores data-driven methodologies that facilitate the
prognostics and health management (PHM) of centrifugal pumps (CPs) while utilizing both …

The raw signals produced by internal gear pumps are susceptible to noises brought on by
mechanical vibrations and the surrounding environment, and the sample count collected …