Untimely machinery breakdown will incur significant losses, especially to the manufacturing
company as it affects the production rates. During operation, machines generate vibrations …

Rotating machinery is widely applied in various types of industrial applications. As a
promising field for reliability of modern industrial systems, early fault diagnosis (EFD) …

Intelligent fault diagnosis is one critical topic of maintenance solution for mechanical
systems. Deep learning models, such as convolutional neural networks (CNNs), have been …

Manufacturing systems are becoming more sophisticated and expensive, particularly with
the development of the intelligent industry. The complexity of the architecture and concept of …

This paper introduces a new condition monitoring approach for extracting fault signatures in
wind turbine blades by utilizing the data from a real-time Supervisory Control and Data …

Given that vibration fault signals collected from industrial circumstances are usually
insufficient and have no labels, supervised learning networks cannot be directly applied to …

Fault detection and diagnosis (FDD) is of utmost importance in ensuring the safety and
reliability of electric vehicles (EVs). The EV's power train and energy storage, namely the …

Vibration-based condition monitoring techniques are commonly used to detect and
diagnose failures of rolling bearings. Accuracy and delay in detecting and diagnosing …

Compound faults and their involved single faults often have severe overlap in traditional
feature spaces, and the strong background noise unavoidably exacerbates the degree of …

Prognostics and health management of the rotating machine aim to use monitoring data to
infer the health conditions of the rotating machine in order to avoid unexpected accidents …