A noise generative network to reduce the gap between simulation and measurement signals in mechanical fault diagnosis

Author:

Wang Hui,Wang Shuhui,Yang Ronggang,Xiang JiaweiORCID

Publisher

Elsevier BV

Reference44 articles.

1. Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature;Benyamin;J. Build. Eng.,2020

2. Application of nonlinear output frequency response functions and deep learning to RV reducer fault diagnosis;Chen;IEEE Trans. Instrum. Meas.,2020

3. Multi-scale split dual calibration network with periodic information for interpretable fault diagnosis of rotating machinery;Chen;Eng. Appl. Artif. Intell.,2023

4. FEM simulation-based generative adversarial networks to detect bearing faults;Gao;IEEE Trans. Ind. Inf.,2020

5. A hybrid of FEM simulations and generative adversarial networks to classify faults in rotor-bearing systems;Gao;ISA Trans.,2021

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