The traditional deep learning-based bearing fault diagnosis approaches assume that the
training and test data follow the same distribution. This assumption, however, is not always …

Untimely machinery breakdown will incur significant losses, especially to the manufacturing
company as it affects the production rates. During operation, machines generate vibrations …

The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …

Intelligent fault detection and diagnosis, as an important approach, play a crucial role in
ensuring the stable, reliable and safe operation of rolling bearings, which is one of the most …

Hydraulic piston pump is known as one of the most critical parts in a typical hydraulic
transmission system. It is imperative to probe into an accurate fault diagnosis method to …

To overcome current challenges in variational mode decomposition (VMD) and its variants
for the fault diagnosis of rotating machines, the decomposing characteristics of two sub …

This review article provides a detailed overview of the measurement and analysis
requirements for transport noise and vibration. It highlights the recommended measurement …

The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …

Vibration signals always contain noise and irregularities, which makes spectrum analysis
difficult to extract high-level features. Recently, graph theory has been applied to spectrum …

Effective detection of fault in rolling bearings with a limited amount of data is essential for the
safe operation of electric machines. This article proposes a novel meta-learning-enabled …