This study presents a comprehensive review of the history of research and development of
different damage-detection methods in the realm of composite structures. Different fields of …

Rotating machinery covers a broad range of mechanical equipment and plays a significant
role in industrial applications. It generally operates under tough working environment and is …

Multi-component extraction is an available method for vibration signal analysis of rotary
machinery, so a novel method of rubbing fault diagnosis based on variational mode …

Singular value decomposition (SVD), as an effective signal denoising tool, has been
attracting considerable attention in recent years. The basic idea behind SVD denoising is to …

A time–frequency analysis method based on ensemble local mean decomposition (ELMD)
and fast kurtogram (FK) is proposed for rotating machinery fault diagnosis. Local mean …

A new bearing vibration feature extraction method based on multiscale permutation entropy
(MPE) and improved support vector machine based binary tree (ISVM-BT) is put forward in …

Fault diagnosis for rolling bearings under variable conditions is a hot and relatively difficult
topic, thus an intelligent fault diagnosis method based on local mean decomposition (LMD) …

The variational mode decomposition (VMD) was proposed recently as an alternative to the
empirical mode decomposition (EMD). To shed further light on its performance, we analyze …

Bearings faults are one of the main causes of breakdown of rotating machines. Thus
detection and diagnosis of mechanical faults in bearings is very crucial for the reliable …

One of the main challenges that the industry faces when dealing with massive data for
failure diagnosis is high dimensionality of such data. This can be tackled by dimensionality …