220 related articles for article (PubMed ID: 35408334)
1. Multi-Stream Convolutional Neural Networks for Rotating Machinery Fault Diagnosis under Noise and Trend Items.
Dong H; Lu J; Han Y
Sensors (Basel); 2022 Apr; 22(7):. PubMed ID: 35408334
[TBL] [Abstract][Full Text] [Related]
2. Bearing Fault Diagnosis via Improved One-Dimensional Multi-Scale Dilated CNN.
He J; Wu P; Tong Y; Zhang X; Lei M; Gao J
Sensors (Basel); 2021 Nov; 21(21):. PubMed ID: 34770636
[TBL] [Abstract][Full Text] [Related]
3. Parallel multi-fusion convolutional neural networks based fault diagnosis of rotating machinery under noisy environments.
Li G; Wu J; Deng C; Chen Z
ISA Trans; 2022 Sep; 128(Pt A):545-555. PubMed ID: 34799098
[TBL] [Abstract][Full Text] [Related]
4. A Fuzzy Fusion Rotating Machinery Fault Diagnosis Framework Based on the Enhancement Deep Convolutional Neural Networks.
Yang D; Karimi HR; Gelman L
Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062632
[TBL] [Abstract][Full Text] [Related]
5. A Novel Anti-Noise Fault Diagnosis Approach for Rolling Bearings Based on Convolutional Neural Network Fusing Frequency Domain Feature Matching Algorithm.
Zhou X; Mao S; Li M
Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450970
[TBL] [Abstract][Full Text] [Related]
6. Time-Frequency Multi-Domain 1D Convolutional Neural Network with Channel-Spatial Attention for Noise-Robust Bearing Fault Diagnosis.
Kim Y; Kim YK
Sensors (Basel); 2023 Nov; 23(23):. PubMed ID: 38067684
[TBL] [Abstract][Full Text] [Related]
7. A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network.
Guo S; Yang T; Gao W; Zhang C
Sensors (Basel); 2018 May; 18(5):. PubMed ID: 29734704
[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. Fault Diagnosis for Rotating Machinery Using Multiscale Permutation Entropy and Convolutional Neural Networks.
Li H; Huang J; Yang X; Luo J; Zhang L; Pang Y
Entropy (Basel); 2020 Jul; 22(8):. PubMed ID: 33286622
[TBL] [Abstract][Full Text] [Related]
10. Bearing Fault Diagnosis Using Multidomain Fusion-Based Vibration Imaging and Multitask Learning.
Hasan MJ; Islam MMM; Kim JM
Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009595
[TBL] [Abstract][Full Text] [Related]
11. Ensemble Dilated Convolutional Neural Network and Its Application in Rotating Machinery Fault Diagnosis.
Cai Y; Wang Z; Yao L; Lin T; Zhang J
Comput Intell Neurosci; 2022; 2022():6316140. PubMed ID: 36188683
[TBL] [Abstract][Full Text] [Related]
12. A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery.
Ma S; Cai W; Liu W; Shang Z; Liu G
Sensors (Basel); 2019 May; 19(10):. PubMed ID: 31137616
[TBL] [Abstract][Full Text] [Related]
13. A New Bearing Fault Diagnosis Method Based on Capsule Network and Markov Transition Field/Gramian Angular Field.
Han B; Zhang H; Sun M; Wu F
Sensors (Basel); 2021 Nov; 21(22):. PubMed ID: 34833837
[TBL] [Abstract][Full Text] [Related]
14. Application of a new one-dimensional deep convolutional neural network for intelligent fault diagnosis of rolling bearings.
Xie S; Ren G; Zhu J
Sci Prog; 2020; 103(3):36850420951394. PubMed ID: 32880535
[TBL] [Abstract][Full Text] [Related]
15. Fault Diagnosis of Rotating Machinery under Noisy Environment Conditions Based on a 1-D Convolutional Autoencoder and 1-D Convolutional Neural Network.
Liu X; Zhou Q; Zhao J; Shen H; Xiong X
Sensors (Basel); 2019 Feb; 19(4):. PubMed ID: 30823579
[TBL] [Abstract][Full Text] [Related]
16. A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals.
Zhang W; Peng G; Li C; Chen Y; Zhang Z
Sensors (Basel); 2017 Feb; 17(2):. PubMed ID: 28241451
[TBL] [Abstract][Full Text] [Related]
17. Bolt-Loosening Detection Using 1D and 2D Input Data Based on Two-Stream Convolutional Neural Networks.
Hou X; Guo W; Ren S; Li Y; Si Y; Su L
Materials (Basel); 2022 Sep; 15(19):. PubMed ID: 36234106
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. An Improved Bearing Fault Diagnosis Model of Variational Mode Decomposition Based on Linked Extension Neural Network.
Wang T; Wang J
Comput Intell Neurosci; 2022; 2022():1615676. PubMed ID: 35510048
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
