Hydraulic systems have the characteristics of strong fault concealment, powerful nonlinear
time-varying signals, and a complex vibration transmission mechanism; hence, diagnosis of …

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 …

The progressive growth in demand and requirements for bearing problem diagnostics in the
operating segment of trains has resulted from an increase in train speed and the …

In the field of data-driven bearing fault diagnosis, convolutional neural network (CNN) has
been widely researched and applied due to its superior feature extraction and classification …

Variational mode decomposition (VMD), a practical adaptive signal decomposition method,
has been widely concerned in the fault detection of rolling bearings. However, the …

In order to enhance the performance of bearing defect classification, feature extraction and
dimensionality reduction have become important. In order to extract the effective features …

The train plug door is the only way for passengers to get on and off. The reliability of the
doors has a direct impact on passengers' safety and operational efficiency. In order to …

Due to constantly varying wind speed, wind turbine (WT) components often operate at
variable speeds in order to capture more energy from wind. As a consequence, WT …

Generally, the transient characteristics of early bearing failure are not obvious. How to
extract weak transient features is a big challenge. Dictionary learning has been successfully …

Gearboxes and induction motors are important components in industrial applications and
their monitoring condition is critical in the industrial sector so as to reduce costs and …