Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …

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

The important part of mechanical equipment is rotating machinery, used mostly in industrial
machinery. Rolling element bearings are the utmost dominant part in rotating machinery, so …

Statistical process control (SPC) is an important tool of enterprise quality management. It can
scientifically distinguish the abnormal fluctuations of product quality. Therefore, intelligent …

Bearings prevent damage caused by frictional forces between parts supporting the rotation
and they keep rotating shafts in their correct position. However, the continuity of work under …

Feature extraction from a signal is the most important step in signal-based fault diagnosis.
Deep learning or deep neural network (DNN) is an effective method to extract features from …

Recognizing why an infant cries is challenging as babies cannot communicate verbally with
others to express their wishes or needs. This leads to difficulties for parents in identifying the …

Neural networks for fault diagnosis need enough samples for training, but in practical
applications, there are often insufficient samples. In order to solve this problem, we propose …

Deep residual networks (DRNs) are a state-of-the-art deep learning model used in the data-
driven fault diagnosis field. Their especially deep architectures give them sufficient capacity …

Estimating the remaining useful life (RUL) of components is a crucial task to enhance
reliability, safety, productivity, and to reduce maintenance cost. In general, predicting the …