Application of a Dense Fusion Attention Network in Fault Diagnosis of Centrifugal Fan

arXiv:2311.07614v2 Announce Type: replace
Abstract: Although the deep learning recognition model has been widely used in the condition monitoring of rotating machinery. However, it is still a challenge to understand the correspondence between the structure and function of the model and the diagnosis process. Therefore, this paper discusses embedding distributed attention modules into dense connections instead of traditional dense cascading operations. It not only decouples the influence of space and channel on fault feature adaptive recalibration feature weights, but also …

abstract application arxiv attention challenge cs.lg deep learning diagnosis function fusion however monitoring network paper process recognition type