296 related articles for article (PubMed ID: 36904745)
1. Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network.
Deng C; Deng Z; Lu S; He M; Miao J; Peng Y
Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904745
[TBL] [Abstract][Full Text] [Related]
2. Intelligent fault identification for industrial automation system via multi-scale convolutional generative adversarial network with partially labeled samples.
Pan T; Chen J; Xie J; Chang Y; Zhou Z
ISA Trans; 2020 Jun; 101():379-389. PubMed ID: 31955949
[TBL] [Abstract][Full Text] [Related]
3. An Intelligent Machinery Fault Diagnosis Method Based on GAN and Transfer Learning under Variable Working Conditions.
He W; Chen J; Zhou Y; Liu X; Chen B; Guo B
Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36501876
[TBL] [Abstract][Full Text] [Related]
4. Imbalanced data fault diagnosis of hydrogen sensors using deep convolutional generative adversarial network with convolutional neural network.
Sun Y; Zhao T; Zou Z; Chen Y; Zhang H
Rev Sci Instrum; 2021 Sep; 92(9):095007. PubMed ID: 34598539
[TBL] [Abstract][Full Text] [Related]
5. Fault Diagnosis of the Rolling Bearing by a Multi-Task Deep Learning Method Based on a Classifier Generative Adversarial Network.
Shen Z; Kong X; Cheng L; Wang R; Zhu Y
Sensors (Basel); 2024 Feb; 24(4):. PubMed ID: 38400448
[TBL] [Abstract][Full Text] [Related]
6. A Rolling Bearing Fault Diagnosis Based on Conditional Depth Convolution Countermeasure Generation Networks under Small Samples.
Peng C; Zhang S; Li C
Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35957215
[TBL] [Abstract][Full Text] [Related]
7. A multi-branch redundant adversarial net for intelligent fault diagnosis of multiple components under drastically variable speeds.
Shi Z; Liu X; Chen J; Zi Y; Zhou Z
ISA Trans; 2022 Oct; 129(Pt A):540-554. PubMed ID: 35109970
[TBL] [Abstract][Full Text] [Related]
8. Bearing Fault Diagnosis with a Feature Fusion Method Based on an Ensemble Convolutional Neural Network and Deep Neural Network.
Li H; Huang J; Ji S
Sensors (Basel); 2019 Apr; 19(9):. PubMed ID: 31052295
[TBL] [Abstract][Full Text] [Related]
9. An Imbalanced Fault Diagnosis Method Based on TFFO and CNN for Rotating Machinery.
Zhang L; Liu Y; Zhou J; Luo M; Pu S; Yang X
Sensors (Basel); 2022 Nov; 22(22):. PubMed ID: 36433352
[TBL] [Abstract][Full Text] [Related]
10. A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Wasserstein Generative Adversarial Network and Convolutional Neural Network under Unbalanced Dataset.
Tang H; Gao S; Wang L; Li X; Li B; Pang S
Sensors (Basel); 2021 Oct; 21(20):. PubMed ID: 34695966
[TBL] [Abstract][Full Text] [Related]
11. Selective kernel convolution deep residual network based on channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis.
Zhang S; Liu Z; Chen Y; Jin Y; Bai G
ISA Trans; 2023 Feb; 133():369-383. PubMed ID: 35798589
[TBL] [Abstract][Full Text] [Related]
12. Intelligent Fault Diagnosis of Rolling Bearing Based on Gramian Angular Difference Field and Improved Dual Attention Residual Network.
Tong A; Zhang J; Xie L
Sensors (Basel); 2024 Mar; 24(7):. PubMed ID: 38610367
[TBL] [Abstract][Full Text] [Related]
13. Gas Sensor Array Fault Diagnosis Based on Multi-Dimensional Fusion, an Attention Mechanism, and Multi-Task Learning.
Huang P; Wang Q; Chen H; Lu G
Sensors (Basel); 2023 Sep; 23(18):. PubMed ID: 37765891
[TBL] [Abstract][Full Text] [Related]
14. Transformer fault diagnosis based on adversarial generative networks and deep stacked autoencoder.
Zhang L; Xu Z; Lu C; Qiao T; Su H; Luo Y
Heliyon; 2024 May; 10(9):e30670. PubMed ID: 38765093
[TBL] [Abstract][Full Text] [Related]
15. TRA-ACGAN: A motor bearing fault diagnosis model based on an auxiliary classifier generative adversarial network and transformer network.
Fu Z; Liu Z; Ping S; Li W; Liu J
ISA Trans; 2024 Jun; 149():381-393. PubMed ID: 38604873
[TBL] [Abstract][Full Text] [Related]
16. Intelligent fault diagnosis of rolling bearings under varying operating conditions based on domain-adversarial neural network and attention mechanism.
Wu H; Li J; Zhang Q; Tao J; Meng Z
ISA Trans; 2022 Nov; 130():477-489. PubMed ID: 35491253
[TBL] [Abstract][Full Text] [Related]
17. Deep network fault diagnosis for imbalanced small-sized samples via a coupled adversarial autoencoder based on the Bayesian method.
Zhang X; Wang Y; Zhou Y; Jia L
Rev Sci Instrum; 2024 May; 95(5):. PubMed ID: 38717264
[TBL] [Abstract][Full Text] [Related]
18. A Gated Recurrent Generative Transfer Learning Network for Fault Diagnostics Considering Imbalanced Data and Variable Working Conditions.
Li Z; Ma J; Wu J; Wong PK; Wang X; Li X
IEEE Trans Neural Netw Learn Syst; 2024 Feb; PP():. PubMed ID: 38356215
[TBL] [Abstract][Full Text] [Related]
19. A Generative Adversarial Network Based a Rolling Bearing Data Generation Method Towards Fault Diagnosis.
Huo L; Qi H; Fei S; Guan C; Li J
Comput Intell Neurosci; 2022; 2022():7592258. PubMed ID: 35875772
[TBL] [Abstract][Full Text] [Related]
20. A Fault Diagnosis Strategy for Analog Circuits with Limited Samples Based on the Combination of the Transformer and Generative Models.
Jia Z; Yang Q; Li Y; Wang S; Xu P; Liu Z
Sensors (Basel); 2023 Nov; 23(22):. PubMed ID: 38005513
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]