BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

407 related articles for article (PubMed ID: 29681393)

  • 1. 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]  

  • 2. 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]  

  • 3. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis.
    Sohaib M; Kim CH; Kim JM
    Sensors (Basel); 2017 Dec; 17(12):. PubMed ID: 29232908
    [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. 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. 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. 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]  

  • 8. 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]  

  • 9. 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]  

  • 10. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.
    Liu J; Hu Y; Wu B; Wang Y; Xie F
    Sensors (Basel); 2017 May; 17(5):. PubMed ID: 28524088
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Novel End-To-End Fault Diagnosis Approach for Rolling Bearings by Integrating Wavelet Packet Transform into Convolutional Neural Network Structures.
    Xiong S; Zhou H; He S; Zhang L; Xia Q; Xuan J; Shi T
    Sensors (Basel); 2020 Sep; 20(17):. PubMed ID: 32887331
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Early Fault Diagnosis of Bearings Using an Improved Spectral Kurtosis by Maximum Correlated Kurtosis Deconvolution.
    Jia F; Lei Y; Shan H; Lin J
    Sensors (Basel); 2015 Nov; 15(11):29363-77. PubMed ID: 26610501
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Application of Teager-Kaiser Energy Operator in the Early Fault Diagnosis of Rolling Bearings.
    Shi X; Zhang Z; Xia Z; Li B; Gu X; Shi T
    Sensors (Basel); 2022 Sep; 22(17):. PubMed ID: 36081131
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A new intelligent bearing fault diagnosis model based on triplet network and SVM.
    Yang K; Zhao L; Wang C
    Sci Rep; 2022 Mar; 12(1):5234. PubMed ID: 35347163
    [TBL] [Abstract][Full Text] [Related]  

  • 15. An enhanced rolling bearing fault detection method combining sparse code shrinkage denoising with fast spectral correlation.
    Li J; Yu Q; Wang X; Zhang Y
    ISA Trans; 2020 Jul; 102():335-346. PubMed ID: 32122637
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network.
    Prosvirin AE; Piltan F; Kim JM
    Sensors (Basel); 2020 Nov; 20(21):. PubMed ID: 33153120
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis.
    Duong BP; Kim JM
    Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29642466
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Rotating Machinery Fault Diagnosis Based on Improved Multiscale Amplitude-Aware Permutation Entropy and Multiclass Relevance Vector Machine.
    Chen Y; Zhang T; Zhao W; Luo Z; Lin H
    Sensors (Basel); 2019 Oct; 19(20):. PubMed ID: 31635428
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 21.