BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

448 related articles for article (PubMed ID: 29904002)

  • 1. Health Degradation Monitoring and Early Fault Diagnosis of a Rolling Bearing Based on CEEMDAN and Improved MMSE.
    Lv Y; Yuan R; Wang T; Li H; Song G
    Materials (Basel); 2018 Jun; 11(6):. PubMed ID: 29904002
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bearing Fault Diagnosis Using Piecewise Aggregate Approximation and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise.
    Hu L; Wang L; Chen Y; Hu N; Jiang Y
    Sensors (Basel); 2022 Sep; 22(17):. PubMed ID: 36081069
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Rolling Bearing Fault Classification Scheme Based on k-Optimized Adaptive Local Iterative Filtering and Improved Multiscale Permutation Entropy.
    Zhang Y; Lv Y; Ge M
    Entropy (Basel); 2021 Feb; 23(2):. PubMed ID: 33562457
    [TBL] [Abstract][Full Text] [Related]  

  • 4. GMPSO-VMD Algorithm and Its Application to Rolling Bearing Fault Feature Extraction.
    Ding J; Huang L; Xiao D; Li X
    Sensors (Basel); 2020 Mar; 20(7):. PubMed ID: 32244305
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fault Feature Extraction Method for Rolling Bearings Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Variational Mode Decomposition.
    Wang L; Li H; Xi T; Wei S
    Sensors (Basel); 2023 Nov; 23(23):. PubMed ID: 38067814
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Fault Feature Extraction and Diagnosis of Rolling Bearings Based on Enhanced Complementary Empirical Mode Decomposition with Adaptive Noise and Statistical Time-Domain Features.
    Zhan L; Ma F; Zhang J; Li C; Li Z; Wang T
    Sensors (Basel); 2019 Sep; 19(18):. PubMed ID: 31546904
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Comprehensive Diagnosis Method of Rolling Bearing Fault Based on CEEMDAN-DFA-Improved Wavelet Threshold Function and QPSO-MPE-SVM.
    Wang Y; Xu C; Wang Y; Cheng X
    Entropy (Basel); 2021 Aug; 23(9):. PubMed ID: 34573767
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An improved complementary ensemble empirical mode decomposition with adaptive noise and its application to rolling element bearing fault diagnosis.
    Cheng Y; Wang Z; Chen B; Zhang W; Huang G
    ISA Trans; 2019 Aug; 91():218-234. PubMed ID: 30738582
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Novel Fault Detection Method for Rolling Bearings Based on Non-Stationary Vibration Signature Analysis.
    Zhen D; Guo J; Xu Y; Zhang H; Gu F
    Sensors (Basel); 2019 Sep; 19(18):. PubMed ID: 31527448
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition.
    Yuan R; Lv Y; Song G
    Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29659510
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A New Method Based on Time-Varying Filtering Intrinsic Time-Scale Decomposition and General Refined Composite Multiscale Sample Entropy for Rolling-Bearing Feature Extraction.
    Ma J; Han S; Li C; Zhan L; Zhang GZ
    Entropy (Basel); 2021 Apr; 23(4):. PubMed ID: 33920417
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Non-contact incipient fault diagnosis method of fixed-axis gearbox based on CEEMDAN.
    Vanraj ; Dhami SS; Pabla BS
    R Soc Open Sci; 2017 Aug; 4(8):170616. PubMed ID: 28879003
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Application of Mutual Information-Sample Entropy Based MED-ICEEMDAN De-Noising Scheme for Weak Fault Diagnosis of Hoist Bearing.
    Yang F; Kou Z; Wu J; Li T
    Entropy (Basel); 2018 Sep; 20(9):. PubMed ID: 33265756
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier.
    Zhou S; Qian S; Chang W; Xiao Y; Cheng Y
    Sensors (Basel); 2018 Jun; 18(6):. PubMed ID: 29899216
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fault diagnosis method of rolling bearings based on adaptive modified CEEMD and 1DCNN model.
    Gao S; Li T; Zhang Y; Pei Z
    ISA Trans; 2023 Sep; 140():309-330. PubMed ID: 37353365
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Fault Diagnosis for Rolling Element Bearings Based on Feature Space Reconstruction and Multiscale Permutation Entropy.
    Zhang W; Zhou J
    Entropy (Basel); 2019 May; 21(5):. PubMed ID: 33267235
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Comprehensive Fault Diagnosis Method for Rolling Bearings Based on Refined Composite Multiscale Dispersion Entropy and Fast Ensemble Empirical Mode Decomposition.
    Zhang W; Zhou J
    Entropy (Basel); 2019 Jul; 21(7):. PubMed ID: 33267394
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Application of EEMD and improved frequency band entropy in bearing fault feature extraction.
    Li H; Liu T; Wu X; Chen Q
    ISA Trans; 2019 May; 88():170-185. PubMed ID: 30558907
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Novel Feature Extraction Method for Power Transformer Vibration Signal Based on CEEMDAN and Multi-Scale Dispersion Entropy.
    Shang H; Xu J; Li Y; Lin W; Wang J
    Entropy (Basel); 2021 Oct; 23(10):. PubMed ID: 34682043
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Intelligent Fault Diagnosis of Rolling Bearings Based on a Complete Frequency Range Feature Extraction and Combined Feature Selection Methodology.
    Xue Z; Huang Y; Zhang W; Shi J; Luo H
    Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960468
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.