Cross-domain data fusion generation: A novel composite label-guided generative solution for adaptation diagnosis

Author:

Zhang TianORCID,Lin Jing,Jiao JinyangORCID,Li HaoORCID

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference37 articles.

1. A survey of fault diagnosis and fault-tolerant techniques-part I: fault diagnosis with model-based and signal-based approaches;Gao;IEEE Trans. Ind. Electron.,2015

2. Applications of machine learning to machine fault diagnosis: a review and roadmap;Lei;Mech. Syst. Signal Process.,2020

3. Intelligent machinery fault diagnosis with event-based camera;Li;IEEE Trans. Ind. Inform.,2024

4. Applications of unsupervised deep transfer learning to intelligent fault diagnosis: a survey and comparative study;Zhao;IEEE Trans. Instrum. Meas.,2021

5. Partial domain adaptation in remaining useful life prediction with incomplete target data;Li;IEEE/ASME Trans. Mechatronics,2023

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