The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …

Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …

Nowadays, condition-based maintenance (CBM) and fault diagnosis (FD) of rotating
machinery (RM) has a vital role in the modern industrial world. However, the remaining …

In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …

There is a constant call for reduction of operational and maintenance costs of induction
motors (IMs). These costs can be significantly reduced if the health of the system is …

Bearing defects have been accepted as one of the major causes of failure in rotating
machinery. It is important to identify and diagnose the failure behavior of bearings for the …

Recently, condition monitoring (CM) and fault detection and diagnosis (FDD) techniques for
rotating machinery (RM) have witnessed substantial advancements in recent decades …

The gear cracks of gear box are one of most common failure forms affecting gear shaft drive.
It has become significant for practice and economy to diagnose the situation of gearbox …

Predictive maintenance is one of the major tasks in today's modern industries. All rotating
machines consisting of rotating elements such as gears, bearings etc are considered as the …

A signal processing method based on friction noise is introduced to predict the tribological
properties of polymers in a wide temperature domain. Three different machine learning …