Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …

Fault diagnosis of rotating machinery plays a significant role for the reliability and safety of
modern industrial systems. As an emerging field in industrial applications and an effective …

In recent years, advances in computer technology and the emergence of big data have
enabled deep learning to achieve impressive successes in bearing condition monitoring …

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 …

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

The paper presents description of bearing, stator and rotor fault diagnostic methods of a
single-phase induction motor. The presented methods use acoustic signals. Five states of …

Effective intelligent fault diagnosis has long been a research focus on the condition
monitoring of rotary machinery systems. Traditionally, time-domain vibration-based fault …

This paper presents the detection of High Impedance Fault (HIF) in solar Photovoltaic (PV)
integrated power system using recurrent neural network-based Long Short-Term Memory …

An article describes an early fault diagnostic technique based on acoustic signals. The
presented technique was used for a single-phase induction motor. The authors measured …

Nowadays, the data-driven diagnosis method, exploiting pattern recognition method to
diagnose the fault patterns automatically, achieves much success for rotating machinery …