Abstract Prognostics and Health Management (PHM), including monitoring, diagnosis,
prognosis, and health management, occupies an increasingly important position in reducing …

Rotating machinery faults can induce characteristic modulation effects in a vibration signal,
and their diagnosis can thus be conducted by extracting fault-induced modulation features …

Intelligent fault diagnosis (IFD) has experienced tremendous progress owing to a great deal
to deep learning (DL)-based methods over the decades. However, the “black box” nature of …

The most existing deep neural networks (DNN)-based methods for fault diagnosis only focus
on prediction accuracy without considering the limitation of labeled sample size. In practical …

Industrial automatic control systems have high requirements for manufacturing accuracy,
which are often adversely affected by the compound fault of rotating machinery such as …

Bearings for rolling elements are essential components of rotating devices and bearing
failure can lead to machine failure. As a result, early identification of such defects, as well as …

With the development of industry and technology, mechanical systems' safety has strong
relations with the diagnosis of bearing faults. Accurate fault diagnosis is essential for the …

In modern diagnostic approaches, the key step consists in generating the features related to
fault type and severity. In fact, the generated features should be able to help the classifier to …

Mechanical intelligent fault diagnosis is an important method to accurately identify the health
status of mechanical equipment. Traditional fault diagnosis methods perform poorly in the …

Bearing fault diagnosis based on the classification of patterns of permutation entropy is
presented in this paper. Patterns of permutation entropy are constructed by using non …