Deep capsule networks based on dual heterogeneous feature resonance fusion for mechanical fault diagnosis
Structural Health Monitoring: An International Journal
Published online on August 11, 2025
Abstract
Structural Health Monitoring, Ahead of Print.
Feature extraction and fusion are important for the fault diagnosis and prediction of rotating machinery. While traditional deep learning networks can learn single attribute of features, they still face difficulties in capturing heterogeneous features ...
Feature extraction and fusion are important for the fault diagnosis and prediction of rotating machinery. While traditional deep learning networks can learn single attribute of features, they still face difficulties in capturing heterogeneous features ...