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 …

Bearing fault diagnosis at early stage is very significant to ensure seamless operation of
induction motors in industrial environment. The identification and classification of faults …

In the machine learning and data science pipelines, feature extraction is considered the
most crucial component according to researchers, where generating a discriminative feature …

Mechanical equipment fault detection is critical in industrial applications. Based on vibration
signal processing and analysis, the traditional fault diagnosis method relies on rich …

Rolling element bearings are widely employed in almost every rotating machine. The health
status of bearings plays an important role in the reliability of rotating machines. This paper …

Featured Application In this paper, the proposed method is validated using experimental
studies based on sound signals for engine fault diagnosis, though ultimately the developed …

With the advent of intelligent manufacturing era, higher requirements are put forward for the
fault diagnosis technology of machinery. The existing data‐driven approaches either rely on …

It is of great significance to accurately obtain the operating state of DC charging equipment
for electric vehicles (Abbreviated as “charging equipment”) and to detect and identify the …

This paper investigates self-powering online condition monitoring for rotating machines by
the piezoelectric transducer as an energy harvester and sensor. The method is devised for …

Intelligent fault diagnosis algorithm for rolling bearings has received increasing attention.
However, in actual industrial environments, most rolling bearings work under severe …