… explored their information fusion in rotating machinery fault diagnosis, they show limited
per… Experiment results demonstrate that the proposed method has promising fault diagnosis …

… a deep network architecture for rotating machinery fault diagnosis. To overcome the
limitations of applying a Transformer and achieve highly accurate fault diagnosis, we establish a …

… Transformer has been widely applied in the research of rotating machinery fault diagnosis
due to its ability to explore the internal correlation of vibration signals. However, challenges …

… researchers in machinery field. Therefore, this review will focus the efforts on fault diagnosis
of rotating machinery. It will place an emphasis on fault diagnosis integrated with deep …

… To enable researchers to fully trust the decisions made by deep diagnostic models,
interpretable rotating machinery fault diagnosis (RMFD) research has emerged. Existing …

… Aiming at the problem of fault diagnosis when there are only … of rotating machinery, this
paper proposes a fault diagnosis … to train the new deep CNN fault diagnosis model so as to …

Many domain adaptation (DA) models have been explored for fault transfer diagnosis. However,
their successes completely rely on the availability of target-domain samples during the …

… With the rapid development of industry, fault diagnosis plays … widely used in the fault diagnosis
of rotating machinery. In the … DL-based intelligent fault diagnosis for rotating machinery. …

… occasional rotating machinery faults, fault signals were difficult to collect in a timely manner.
There was an imbalanced volume of data in the fault diagnosis training model, and the fault …

… Background of diagnosis With the increasing complexity, rotating machinery fault diagnosis
play a … Rotating components such as planetary gears and rolling bearings always have high …