Rotating machines is an essential part of any manufacturing industry. The sudden
breakdown of such machines due to improper maintenance can also lead to the industries' …

Gear fault diagnosis (GFD) based on vibration signals is a popular research topic in industry
and academia. This paper provides a comprehensive summary and systematic review of …

Rolling bearing is the key supporting component of aero-engines, of which fault diagnosis is
very important to ensure its reliable operation and continuous airworthiness. However, the …

Rotating machines are frequently used in industrial applications. However, due to their
severity, mechanical failures such as rotor imbalance, shaft imbalance, pulley imbalance …

This study involved a systematic literature review using bibliometric analysis to examine the
evolution and current trends of Markov switching studies. The bibliometric analysis was used …

Deep learning-based fault diagnosis models achieve great success with sufficient balanced
data, but the imbalanced dataset in real industrial scenarios will seriously affect the …

This paper proposes a new narrow-band filtering algorithm to improve the problem of TVF-
EMD algorithm decomposing too many narrow-bands. The algorithm uses the energy …

The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the
distribution of the features they induce. In particular, knowing the joint distribution of the pair …

Extracting representative feature sets from raw signals is crucial in Prognostics and Health
Management (PHM) for components' behavior understanding. The literature proposes …

Reciprocating compressors and centrifugal pumps are rotating machines used in industry,
where fault detection is crucial for avoiding unnecessary and costly downtime. A novel …