BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

160 related articles for article (PubMed ID: 33267068)

  • 1. An Integrated Approach Based on Swarm Decomposition, Morphology Envelope Dispersion Entropy, and Random Forest for Multi-Fault Recognition of Rolling Bearing.
    Wan S; Peng B
    Entropy (Basel); 2019 Apr; 21(4):. PubMed ID: 33267068
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Intelligent Diagnosis of Rolling Element Bearing Based on Refined Composite Multiscale Reverse Dispersion Entropy and Random Forest.
    Liu A; Yang Z; Li H; Wang C; Liu X
    Sensors (Basel); 2022 Mar; 22(5):. PubMed ID: 35271193
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. A Bearing Fault Diagnosis Method Based on PAVME and MEDE.
    Yan X; Xu Y; She D; Zhang W
    Entropy (Basel); 2021 Oct; 23(11):. PubMed ID: 34828100
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Fault Diagnosis for Rolling Bearings Based on Fine-Sorted Dispersion Entropy and SVM Optimized with Mutation SCA-PSO.
    Fu W; Tan J; Xu Y; Wang K; Chen T
    Entropy (Basel); 2019 Apr; 21(4):. PubMed ID: 33267118
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Novel Method Based on Multi-Island Genetic Algorithm Improved Variational Mode Decomposition and Multi-Features for Fault Diagnosis of Rolling Bearing.
    Liang T; Lu H
    Entropy (Basel); 2020 Sep; 22(9):. PubMed ID: 33286764
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Research on Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition Improved by the Niche Genetic Algorithm.
    Shi R; Wang B; Wang Z; Liu J; Feng X; Dong L
    Entropy (Basel); 2022 Jun; 24(6):. PubMed ID: 35741545
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Novel Fault Diagnosis Method for Rolling Bearing Based on Hierarchical Refined Composite Multiscale Fluctuation-Based Dispersion Entropy and PSO-ELM.
    Chen Y; Yuan Z; Chen J; Sun K
    Entropy (Basel); 2022 Oct; 24(11):. PubMed ID: 36359611
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. Weak Fault Feature Extraction of Rolling Bearings Based on Adaptive Variational Modal Decomposition and Multiscale Fuzzy Entropy.
    Lv Z; Han S; Peng L; Yang L; Cao Y
    Sensors (Basel); 2022 Jun; 22(12):. PubMed ID: 35746283
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Fault Diagnosis of a Rolling Bearing Based on Adaptive Sparest Narrow-Band Decomposition and RefinedComposite Multiscale Dispersion Entropy.
    Luo S; Yang W; Luo Y
    Entropy (Basel); 2020 Mar; 22(4):. PubMed ID: 33286149
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An Early Fault Diagnosis Method of Rolling Bearings on the Basis of Adaptive Frequency Window and Sparse Coding Shrinkage.
    Wan S; Peng B
    Entropy (Basel); 2019 Jun; 21(6):. PubMed ID: 33267298
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A new fault feature extraction method of rolling bearings based on the improved self-selection ICEEMDAN-permutation entropy.
    Xiao M; Wang Z; Zhao Y; Geng G; Dustdar S; Donta PK; Ji G
    ISA Trans; 2023 Dec; 143():536-547. PubMed ID: 37770368
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Rolling Bearing Fault Diagnosis Based on VMD-MPE and PSO-SVM.
    Ye M; Yan X; Jia M
    Entropy (Basel); 2021 Jun; 23(6):. PubMed ID: 34208777
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Fault Diagnosis Approach for Rolling Bearing Integrated SGMD, IMSDE and Multiclass Relevance Vector Machine.
    Yan X; Liu Y; Jia M
    Sensors (Basel); 2020 Aug; 20(15):. PubMed ID: 32759788
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Fault Diagnosis for Rolling Bearing of Combine Harvester Based on Composite-Scale-Variable Dispersion Entropy and Self-Optimization Variational Mode Decomposition Algorithm.
    Jiang W; Shan Y; Xue X; Ma J; Chen Z; Zhang N
    Entropy (Basel); 2023 Jul; 25(8):. PubMed ID: 37628141
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. Research on rolling bearing fault diagnosis based on multi-dimensional feature extraction and evidence fusion theory.
    Li J; Ying Y; Ren Y; Xu S; Bi D; Chen X; Xu Y
    R Soc Open Sci; 2019 Feb; 6(2):181488. PubMed ID: 30891276
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.