Fault detection and diagnosis play a crucial role in ensuring the reliability and safety of
modern industrial systems. For safety and cost considerations, critical equipment and …

Mechanical fault diagnosis is crucial for ensuring the normal operation of mechanical
equipment. With the rapid development of deep learning technology, the methods based on …

For the poor model generalization and low diagnostic efficiency of fault diagnosis under
imbalanced distributions, a novel fault diagnosis method using variational autoencoder …

The extreme unbalance of training samples among different working conditions caused by
complex and variable external environments makes the fault diagnosis of a chiller based on …

As vital equipment in modern industry, the health state of rotating machinery influences the
production process and equipment safety. However, rotating machinery generally operates …

Rotating machinery operates continuously for long periods of time under varying conditions
in actual industrial environments. The number of fault samples increases with equipment …

Transfer learning (TL) and generative adversarial networks (GANs) have been widely
applied to intelligent fault diagnosis under imbalanced data and different working conditions …

Due to the reality that it is difficult to collect sufficient and balanced data for all fault types of
rolling bearings, it is a challenging mission to accurately realize the rolling bearing fault …

Due to the limited fault samples, the accuracy of the bearing fault diagnosis model is
challenged. Therefore, this article proposes a bearing fault diagnosis method based on …

Timely and accurate fault diagnosis of transmission systems is crucial to ensuring the
systems' reliability, safety, and economic viability. However, intelligent fault diagnosis …