These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 33965200)

  • 1. Intelligent vibration signal denoising method based on non-local fully convolutional neural network for rolling bearings.
    Han H; Wang H; Liu Z; Wang J
    ISA Trans; 2022 Mar; 122():13-23. PubMed ID: 33965200
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Multi-layer convolutional dictionary learning network for signal denoising and its application to explainable rolling bearing fault diagnosis.
    Qin Y; Yang R; He B; Chen D; Mao Y
    ISA Trans; 2024 Apr; 147():55-70. PubMed ID: 38309975
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Fault Diagnosis of Rolling Bearings Based on a Residual Dilated Pyramid Network and Full Convolutional Denoising Autoencoder.
    Shi H; Chen J; Si J; Zheng C
    Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33050210
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. The Fault Diagnosis of Rolling Bearings Is Conducted by Employing a Dual-Branch Convolutional Capsule Neural Network.
    Lu W; Liu J; Lin F
    Sensors (Basel); 2024 May; 24(11):. PubMed ID: 38894172
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples.
    Yang D; Karimi HR; Sun K
    Neural Netw; 2021 Sep; 141():133-144. PubMed ID: 33901878
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Intelligent Defect Diagnosis of Rolling Element Bearings under Variable Operating Conditions Using Convolutional Neural Network and Order Maps.
    Tayyab SM; Chatterton S; Pennacchi P
    Sensors (Basel); 2022 Mar; 22(5):. PubMed ID: 35271173
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Attention-guided joint learning CNN with noise robustness for bearing fault diagnosis and vibration signal denoising.
    Wang H; Liu Z; Peng D; Cheng Z
    ISA Trans; 2022 Sep; 128(Pt B):470-484. PubMed ID: 34961609
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Novel Deep Learning Model for the Detection and Identification of Rolling Element-Bearing Faults.
    Shenfield A; Howarth M
    Sensors (Basel); 2020 Sep; 20(18):. PubMed ID: 32911771
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. New Fault Diagnosis Method for Rolling Bearings Based on Improved Residual Shrinkage Network Combined with Transfer Learning.
    Sun T; Gao J
    Sensors (Basel); 2024 Sep; 24(17):. PubMed ID: 39275611
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Intelligent fault diagnosis algorithm of rolling bearing based on optimization algorithm fusion convolutional neural network.
    Wang Q; Sun Z; Zhu Y; Song C; Li D
    Math Biosci Eng; 2023 Nov; 20(11):19963-19982. PubMed ID: 38052632
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Intelligent Rolling Bearing Fault Diagnosis Method Using Symmetrized Dot Pattern Images and CBAM-DRN.
    Cui W; Meng G; Gou T; Wang A; Xiao R; Zhang X
    Sensors (Basel); 2022 Dec; 22(24):. PubMed ID: 36560323
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Fault diagnosis of rolling bearings with recurrent neural network-based autoencoders.
    Liu H; Zhou J; Zheng Y; Jiang W; Zhang Y
    ISA Trans; 2018 Jun; 77():167-178. PubMed ID: 29681393
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. A Bearing Fault Diagnosis Method Based on Wavelet Packet Transform and Convolutional Neural Network Optimized by Simulated Annealing Algorithm.
    He F; Ye Q
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214312
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Rolling Bearing Fault Diagnosis Based on Markov Transition Field and Residual Network.
    Yan J; Kan J; Luo H
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632345
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.