Rolling element bearings play a crucial role in the functioning of rotating machinery.
Recently, the use of diagnostics and prognostics methodologies assisted by artificial …

Medium-voltage (MV) induction motors are widely used in the industry and are essential to
industrial processes. The breakdown of these MV motors not only leads to high repair …

Rotating machinery intelligent diagnosis with large data has been researched
comprehensively, while there is still a gap between the existing diagnostic model and the …

This paper presents a benchmark data set for condition monitoring of rolling bearings in
combination with an extensive description of the corresponding bearing damage, the data …

This paper proposes an intelligent method based on artificial neural networks (ANNs) to
detect bearing defects of induction motors. In this method, the vibration signal passes …

The ensemble empirical mode decomposition (EEMD) can overcome the mode mixing
problem of the empirical mode decomposition (EMD) and therefore provide more precise …

At present, the fourth industrial revolution is pushing factories toward an intelligent,
interconnected grid of machinery, communication systems, and computational resources …

This paper proposes a systematic procedure based on a pattern recognition technique for
fault diagnosis of induction motors bearings through the artificial neural networks (ANNs). In …

Using deep learning in three-phase induction motor fault diagnosis has gained increasing
interest nowadays. This paper proposes a Convolutional Neural Network (CNN) model to …

A bearing is a key component in rotating machinery. The prompt monitoring of a bearings'
condition is critical for the reduction of mechanical accidents. With the rapid development of …