A multi-source domain information fusion network for rotating machinery fault diagnosis under variable operating conditions
Author:
Publisher
Elsevier BV
Subject
Hardware and Architecture,Information Systems,Signal Processing,Software
Reference50 articles.
1. CFCNN: A novel convolutional fusion framework for collaborative fault identification of rotating machinery;Xu;Inform. Fusion,2023
2. Deep discriminative transfer learning network for cross-machine fault diagnosis;Qian;Mech. Syst. Signal Process.,2023
3. A fault location method based on ensemble complex spatio-temporal attention network for complex systems under fluctuating operating condition;Yang;Appl. Soft. Comput.,2023
4. A review of the application of deep learning in intelligent fault diagnosis of rotating machinery;Zhu;Measurement,2023
5. An intelligent fault diagnosis scheme for rotating machinery based on supervised domain adaptation with manifold embedding;Xu;IEEE Internet Things,2022
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