The improvements in wind energy infrastructure have been a constant process throughout
many decades. There are new advancements in technology that can further contribute …

The rolling bearing is a key element of rotating machine and its fault diagnosis is a research
focus. When a single fault of a rolling bearing fails to be addressed in time, it will cause …

Deep learning‐based fault diagnosis of rolling bearings is a hot research topic, and a rapid
and accurate diagnosis is important. In this paper, aiming at the vibration image samples of …

This paper aims at the development of a method for monitoring oil debris as well as oil
viscosity, using the optical measurement. An on-line optical oil debris sensor is designed …

Neural networks (NNs) have attracted a lot of attention in recent years in automated
condition monitoring assessment. Scientists have successfully demonstrated that NNs can …

Friction-induced wear debris from joint implants are effective resources in investigating
artificial joint wear and cellular immune response mechanisms. To improve the accuracy of …

This article proposes a novel approach to address the issues of low accuracy in fault
diagnosis and the difficulty in installing sensors on rolling bearings in mechanical and …

Abstract Three-dimensional (3D) surfaces of wear particles were reconstructed through multi-
view contour fitting and dense point-cloud interpolation with an aim to obtain comprehensive …

Lubricating oil monitoring technology is a commonly used method in aeroengine condition
monitoring, which includes particle counting technology, as well as spectral and ferrography …

This work is focused on single word Arabic automatic speech recognition (AASR). Two
techniques are used during the feature extraction phase; Log frequency spectral coefficients …