With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

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

Fault diagnosis of wind turbine gearboxes is crucial in ensuring wind farms' reliability and
safety. However, nonstationary working conditions, such as load change or speed …

Fault diagnosis of the bearing is vital for the safe and reliable operation of rotating machines
in the manufacturing industry. Convolutional neural networks (CNNs) have been popular in …

Convolutional neural networks, with a powerful ability for feature representation, have made
vast inroads into motor fault diagnosis. However, most of the existing CNN models cannot …

This paper proposes a selective kernel convolution deep residual network based on the
channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis. First …

CNN-based fault diagnosis approaches have achieved promising results in improving the
safety and reliability of rotating machinery. Most of the existing CNN models are developed …

In recent years, deep learning has been proved to be a promising bearing fault diagnosis
technology. However, most of the existing methods are based on single-task learning. Fault …

In industrial production, it is particularly important to diagnose the bearing fault in time under
variable loads. The intelligent diagnosis method has strong robustness without human …

Recently, deep learning-based intelligent fault diagnosis methods have been developed
rapidly, which rely on massive data to train the diagnosis model. However, it is usually …