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 …

In the era of healthcare, and its related research fields, the dimensionality problem of high
dimensional data is a massive challenge as it contains a huge number of variables forming …

In order to achieve effective online detection of bearing incipient fault, it's necessary to
adaptively extract representative features to incipient fault. However, the traditional feature …

Deep neural networks exhibit excellent performance in fault feature extraction for
considerable amounts of data. However, data labeling is a difficult task in practical …

This paper presents a new online detection approach for rolling bearing's incipient fault
based on self-adaptive deep feature matching (SDFM). This approach includes offline and …

Although researchers have made substantial progress in bearing fault detection and
diagnosis recently, incipient fault detection, especially online detection, is still at an initial …

Abstract Condition Monitoring System (CMS) substantiates potential economic benefits and
enables prognostic maintenance in wind turbine-generator failure prevention. Vibration …

In this paper, an innovative hybrid fault monitoring scheme integrating the manifold learning
and the isolation forest was established to monitor the state of marine diesel engine. The …

As an outstanding discriminant analysis technique, Fisher discriminant analysis (FDA)
gained extensive attention in supervised dimensionality reduction and fault diagnosis fields …

The primary task of rotating machinery fault diagnosis is to extract more fault feature
information from the measured signals, so that its diagnostic result is more accurate and …