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 …

Prognostics and health management is an emerging discipline to scientifically manage the
health condition of engineering systems and their critical components. It mainly consists of …

Rotating equipment is considered as a key component in several industrial sectors. In fact,
the continuous operation of many industrial machines such as sub-sea pumps and gas …

This paper presents an empirical study of feature extraction methods for the application of
low-speed slew bearing condition monitoring. The aim of the study is to find the proper …

In recent years, deep learning technique has been used in mechanical intelligent fault
diagnosis and it has achieved much success. Among the deep learning models …

This paper presents a novel hybrid model for fault detection and classification of motor
bearing. In the proposed model, permutation entropy (PE) of the vibration signal is …

To timely detect the incipient failure of rolling bearing and find out the accurate fault location,
a novel rolling bearing fault diagnosis method is proposed based on the composite …

Intelligent fault diagnosis of rotating machinery is essentially a pattern recognition problem.
Meanwhile, effective feature extraction from the raw vibration signal is an important …

The rolling element bearing is one of the most critical components that determine the
machinery health and its remaining lifetime in modern production machinery. Robust …

This paper is to provide practical options for prognostics so that beginners can select
appropriate methods for their fields of application. To achieve this goal, several popular …