320 related articles for article (PubMed ID: 33647055)
1. A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing.
Wu C; Zeng Z
PLoS One; 2021; 16(3):e0246905. PubMed ID: 33647055
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Reliable Fault Diagnosis of Bearings Using an Optimized Stacked Variational Denoising Auto-Encoder.
Yan X; Xu Y; She D; Zhang W
Entropy (Basel); 2021 Dec; 24(1):. PubMed ID: 35052062
[TBL] [Abstract][Full Text] [Related]
5. Combine Harvester Bearing Fault-Diagnosis Method Based on SDAE-RCmvMSE.
Yang G; Cheng Y; Xi C; Liu L; Gan X
Entropy (Basel); 2022 Aug; 24(8):. PubMed ID: 36010803
[TBL] [Abstract][Full Text] [Related]
6. Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis.
Faysal A; Ngui WK; Lim MH; Leong MS
Sensors (Basel); 2021 Dec; 21(23):. PubMed ID: 34884120
[TBL] [Abstract][Full Text] [Related]
7. GAN-SAE based fault diagnosis method for electrically driven feed pumps.
Han H; Hao L; Cheng D; Xu H
PLoS One; 2020; 15(10):e0239070. PubMed ID: 33091004
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. 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]
12. A Transfer Learning Framework with a One-Dimensional Deep Subdomain Adaptation Network for Bearing Fault Diagnosis under Different Working Conditions.
Zhang R; Gu Y
Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214528
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. The Novel Sensor Network Structure for Classification Processing Based on the Machine Learning Method of the ACGAN.
Chen Y; Tao J; Wang J; Chen X; Xie J; Xiong J; Yang K
Sensors (Basel); 2019 Jul; 19(14):. PubMed ID: 31319556
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Multi-Representation Domain Adaptation Network with Duplex Adversarial Learning for Hot-Rolling Mill Fault Diagnosis.
Peng R; Zhang X; Shi P
Entropy (Basel); 2022 Dec; 25(1):. PubMed ID: 36673223
[TBL] [Abstract][Full Text] [Related]
17. A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery.
Gao Y; Piltan F; Kim JM
Sensors (Basel); 2022 Oct; 22(19):. PubMed ID: 36236633
[TBL] [Abstract][Full Text] [Related]
18. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.
Lu C; Wang Y; Ragulskis M; Cheng Y
PLoS One; 2016; 11(10):e0164111. PubMed ID: 27711246
[TBL] [Abstract][Full Text] [Related]
19. Deep residual learning-based fault diagnosis method for rotating machinery.
Zhang W; Li X; Ding Q
ISA Trans; 2019 Dec; 95():295-305. PubMed ID: 30598323
[TBL] [Abstract][Full Text] [Related]
20. A Robust Deep Neural Network for Rolling Element Fault Diagnosis under Various Operating and Noisy Conditions.
Lee CY; Zhuo GL; Le TA
Sensors (Basel); 2022 Jun; 22(13):. PubMed ID: 35808201
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
