Rotating machinery is widely applied in various types of industrial applications. As a
promising field for reliability of modern industrial systems, early fault diagnosis (EFD) …

The increasing integration and complexity of rotating machinery have led to the difficulty of
its fault diagnosis. Condition-based maintenance (CBM) strategy is becoming more and …

The vibration signals collected from rolling bearing are usually complex and non-stationary
with heavy background noise. Therefore, it is a great challenge to efficiently learn the …

The traditional on-house sensing (OHS) accelerometer for vibration measurements causes
poor signal-to-noise ratio (SNR) and complicated fault modulations, which increases the …

The bearing vibration signal with strong non-stationary properties is normally composed of
multiple components (eg periodic impulses, background noise and other external signal) …

Early fault diagnosis of rolling bearings is crucial to operating and maintenance cost
reduction of the equipment with bearings. This paper aims to propose a novel early fault …

The rolling bearing is a crucial component of the rotating machine, and it is particularly vital
to ensure its normal operation. In addition, the selection of different category features will …

Harmonic product spectrum (HPS) is an important tool in bearing fault diagnosis because it
can quickly locate the fault resonance frequency band. However, its frequency band division …

The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can
decompose signals into several narrow-band components, which is advantageous to …

Wheelset-bearing is an important part of the bogie for high-speed train. Fault diagnosis of
wheelset-bearing is of great significance for the safety of the railway service. In the diagnosis …