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 *

123 related articles for article (PubMed ID: 35957238)

  • 41. 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]  

  • 42. Adaptive online dictionary learning for bearing fault diagnosis.
    Lu Y; Xie R; Liang SY
    Int J Adv Manuf Technol; 2019 Mar; 101(1-4):195-202. PubMed ID: 31182896
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Rolling Bearing Incipient Fault Diagnosis Method Based on Improved Transfer Learning with Hybrid Feature Extraction.
    Yang Z; Yang R; Huang M
    Sensors (Basel); 2021 Nov; 21(23):. PubMed ID: 34883892
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Research on the Rapid Diagnostic Method of Rolling Bearing Fault Based on Cloud-Edge Collaboration.
    Tang X; Xu L; Chen G
    Entropy (Basel); 2022 Sep; 24(9):. PubMed ID: 36141163
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Fault Diagnosis of Rolling Element Bearings with a Two-Step Scheme Based on Permutation Entropy and Random Forests.
    Xue X; Li C; Cao S; Sun J; Liu L
    Entropy (Basel); 2019 Jan; 21(1):. PubMed ID: 33266812
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Fault Diagnosis for Rolling Bearings Using Optimized Variational Mode Decomposition and Resonance Demodulation.
    Zhang C; Wang Y; Deng W
    Entropy (Basel); 2020 Jul; 22(7):. PubMed ID: 33286510
    [TBL] [Abstract][Full Text] [Related]  

  • 47. 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]  

  • 48. 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]  

  • 49. Multiscale Distribution Entropy and t-Distributed Stochastic Neighbor Embedding-Based Fault Diagnosis of Rolling Bearings.
    Tu D; Zheng J; Jiang Z; Pan H
    Entropy (Basel); 2018 May; 20(5):. PubMed ID: 33265449
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Application of higher order spectral features and support vector machines for bearing faults classification.
    Saidi L; Ben Ali J; Fnaiech F
    ISA Trans; 2015 Jan; 54():193-206. PubMed ID: 25282095
    [TBL] [Abstract][Full Text] [Related]  

  • 51. An improved incipient fault detection method based on Kullback-Leibler divergence.
    Chen H; Jiang B; Lu N
    ISA Trans; 2018 Aug; 79():127-136. PubMed ID: 29801923
    [TBL] [Abstract][Full Text] [Related]  

  • 52. 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]  

  • 53. Research on Extraction of Compound Fault Characteristics for Rolling Bearings in Wind Turbines.
    Xiang L; Su H; Li Y
    Entropy (Basel); 2020 Jun; 22(6):. PubMed ID: 33286455
    [TBL] [Abstract][Full Text] [Related]  

  • 54. A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D-S Evidence Theory.
    Lu J; Zhang H; Tang X
    Entropy (Basel); 2019 Jul; 21(7):. PubMed ID: 33267401
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Rolling Bearing Fault Diagnosis Based on WOA-VMD-MPE and MPSO-LSSVM.
    Jin Z; Chen G; Yang Z
    Entropy (Basel); 2022 Jul; 24(7):. PubMed ID: 35885150
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Incipient fault detection of rolling bearing using maximum autocorrelation impulse harmonic to noise deconvolution and parameter optimized fast EEMD.
    Zheng K; Luo J; Zhang Y; Li T; Wen J; Xiao H
    ISA Trans; 2019 Jun; 89():256-271. PubMed ID: 30587330
    [TBL] [Abstract][Full Text] [Related]  

  • 57. On the Accuracy of Fault Diagnosis for Rolling Element Bearings Using Improved DFA and Multi-Sensor Data Fusion Method.
    Song Q; Zhao S; Wang M
    Sensors (Basel); 2020 Nov; 20(22):. PubMed ID: 33198252
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Adaptive Multiclass Mahalanobis Taguchi System for Bearing Fault Diagnosis under Variable Conditions.
    Wang N; Wang Z; Jia L; Qin Y; Chen X; Zuo Y
    Sensors (Basel); 2018 Dec; 19(1):. PubMed ID: 30577670
    [TBL] [Abstract][Full Text] [Related]  

  • 59. MVMD-MOMEDA-TEO Model and Its Application in Feature Extraction for Rolling Bearings.
    Li Z; Ma J; Wang X; Wu J
    Entropy (Basel); 2019 Mar; 21(4):. PubMed ID: 33267045
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Vibration sensor-based bearing fault diagnosis using ellipsoid-ARTMAP and differential evolution algorithms.
    Liu C; Wang G; Xie Q; Zhang Y
    Sensors (Basel); 2014 Jun; 14(6):10598-618. PubMed ID: 24936949
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.