Safety and reliability of large critical infrastructure such as long-span bridges, high-rise
buildings, nuclear power plants, high-voltage transmission towers, rotating machinery, and …

Enormous data are continuously collected by the structural health monitoring system of civil
infrastructures. The structural health monitoring data inevitably involve anomalies caused by …

Deep learning-based approaches for diagnosing bearing faults have attracted considerable
attention in the last years. However, in real-world applications, these methods face …

With the rise of industrial artificial intelligence (AI), smart sensing, and the Internet of Things
(IoT), companies are learning how to use their data not only for analysing the past but also …

Accurate fault prediction of rolling bearing can predict the operation condition in advance,
which is an important means to ensure the safety and reliability of rotating machinery. Aimed …

This article presents the experimental and statistical methodology for localized fault analysis
in the rotor-bearing system. These defects on outer race, on inner race, and on a …

Aiming at raw vibration signal of rolling bearing with long time series, a fault diagnosis
model based on multimodal data fusion and deep belief network is proposed in this paper …

Accurate fault diagnosis of rolling bearing is a necessary means to ensure the safe and
reliable operation of mechanical equipment. In this paper, a fault diagnosis method based …

Purpose The purpose of this study is to achieve an accurate intelligent fault diagnosis of
rolling bearing. Design/methodology/approach To extract deep features of the original …

The remaining useful life (RUL) prediction of rolling bearings is of great significance in
engineering industries. Support vector regression (SVR) is a widely used machine learning …