Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …

The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …

For data mining tasks on high-dimensional data, feature selection is a necessary pre-
processing stage that plays an important role in removing redundant or irrelevant features …

The monitoring of rotating machinery is an essential task in today's production processes.
Currently, several machine learning and deep learning-based modules have achieved …

Contactless fault diagnosis is one of the most important technique for fault identification of
equipment. Based on the idea of contactless fault diagnosis, this paper presents a sound …

Feature selection (FS) is an important data processing method in pattern recognition and
data mining. Due to not considering characteristics of the FS problem itself, traditional …

The failure of a rolling bearing may cause the shutdown of mechanical equipment and even
induce catastrophic accidents, resulting in tremendous economic losses and a severely …

Railway point machines (RPMs) is one of the most vital devices closely related to the
efficiency and safety of train operation. Considering the advantages of contactlessness and …

Traditional feature extraction methods are used to extract the features of signal to construct
the fault feature matrix, which exists the complex structure, higher correlation, and …

Feature selection (FS), as one of the most significant preprocessing techniques in the fields
of machine learning and pattern recognition, has received great attention. In recent years …