This paper puts into perspective the state-of-the art knowledge on bearing currents and
diagnosis tools, which rely on shaft voltages and bearing currents phenomena. Today, shaft …

In the last decade, the adoption of technological tools in manufacturing industry, such as the
use of the Internet of Things (IoT) and Machine Learning (ML), has led to the advent of the …

The prognosis of bearings is vital for condition-based maintenance of rotating machinery.
This article proposes a systematic prognostic scheme for rolling element bearings. The …

Deep learning with ability to feature learning and nonlinear function approximation has
shown its effectiveness for machine fault prediction. While, how to transfer a deep network …

Fault diagnosis and prognosis are some of the most crucial functionalities in complex and
safety-critical engineering systems, and particularly fault diagnosis, has been a subject of …

The degradation of bearings plays a key role in the failures of industrial machinery.
Prognosis of bearings is critical in adopting an optimal maintenance strategy to reduce the …

Rolling bearings are the key components of rotating machinery. Thus, the prediction of
remaining useful life (RUL) is vital in condition-based maintenance (CBM). This paper …

Machine health monitoring is of great importance in industrial informatics field. Recently,
deep learning methods applied to machine health monitoring have been proven effective …

This paper presents a data-driven prognostic framework for rolling-element bearings
(REBs). This framework infers a bearing's health index by defining a degree-of …

This paper focuses on the development of an integrated scheme for diagnosing bearing
defects in induction motors, under the class-imbalanced condition. This scheme comprises …