Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …

As vital components of diesel engines, failure issues of cylinder liner-piston ring components
(CLPRs), which work under harsh conditions of high temperature, high pressure, and heavy …

This paper presents a convolutional neural network (CNN) based approach for fault
diagnosis of rotating machinery. The proposed approach incorporates sensor fusion by …

This paper deals with the state-of-the-art strategies and techniques based on vibro-acoustic
signals that can monitor and diagnose malfunctions in Internal Combustion Engines (ICEs) …

Bearing fault diagnosis is essential in manufacturing systems to avoid problems such as
downtime costs. Convolutional neural network (CNN) models have enabled a new …

Bearings are fundamental mechanical components in rotary machines (engines, gearboxes,
generators, radars, turbines, etc.) that have been identified as one of the primary causes of …

Accurate and timely bearing fault diagnosis is crucial to decrease the probability of
unexpected failures of rotating machinery and improve the efficiency of its scheduled …

Area of application of rotating machinery in day to day life, and for industrial use in
manufacturing and processes, nuclear power station, automobile, oil & gas refinery etc has …

A step-by-step fuzzy diagnostic method based on frequency-domain symptom extraction and
trivalent logic fuzzy diagnosis theory (TLFD), which is established by combining the trivalent …

Bearings are one of the most critical elements in rotating machinery systems. Bearing faults
are the main reason for failures in electrical motors and generators. Therefore, early bearing …