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 *

131 related articles for article (PubMed ID: 36981303)

  • 41. A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals.
    Zhang W; Peng G; Li C; Chen Y; Zhang Z
    Sensors (Basel); 2017 Feb; 17(2):. PubMed ID: 28241451
    [TBL] [Abstract][Full Text] [Related]  

  • 42. A Multiscale Spatio-Temporal Convolutional Deep Belief Network for Sensor Fault Detection of Wind Turbine.
    Wang H; Wang H; Jiang G; Wang Y; Ren S
    Sensors (Basel); 2020 Jun; 20(12):. PubMed ID: 32599907
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Automatic Feature Extraction and Construction Using Genetic Programming for Rotating Machinery Fault Diagnosis.
    Peng B; Wan S; Bi Y; Xue B; Zhang M
    IEEE Trans Cybern; 2021 Oct; 51(10):4909-4923. PubMed ID: 33237874
    [TBL] [Abstract][Full Text] [Related]  

  • 44. The Improved WNOFRFs Feature Extraction Method and Its Application to Quantitative Diagnosis for Cracked Rotor Systems.
    Liang H; Zhao C; Chen Y; Liu Y; Zhao Y
    Sensors (Basel); 2022 Mar; 22(5):. PubMed ID: 35271084
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Self-Supervised Joint Learning Fault Diagnosis Method Based on Three-Channel Vibration Images.
    Zhang W; Chen D; Kong Y
    Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300516
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Deep residual learning-based fault diagnosis method for rotating machinery.
    Zhang W; Li X; Ding Q
    ISA Trans; 2019 Dec; 95():295-305. PubMed ID: 30598323
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Transfer Relation Network for Fault Diagnosis of Rotating Machinery With Small Data.
    Lu N; Hu H; Yin T; Lei Y; Wang S
    IEEE Trans Cybern; 2022 Nov; 52(11):11927-11941. PubMed ID: 34156958
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Research on gearbox temperature field image fault diagnosis method based on transfer learning and deep belief network.
    Lu X; Li P
    Sci Rep; 2023 Apr; 13(1):6664. PubMed ID: 37095134
    [TBL] [Abstract][Full Text] [Related]  

  • 49. 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]  

  • 50. Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application.
    Han T; Liu C; Yang W; Jiang D
    ISA Trans; 2020 Feb; 97():269-281. PubMed ID: 31420125
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Bearing Fault Diagnosis Method Based on Deep Convolutional Neural Network and Random Forest Ensemble Learning.
    Xu G; Liu M; Jiang Z; Söffker D; Shen W
    Sensors (Basel); 2019 Mar; 19(5):. PubMed ID: 30832449
    [TBL] [Abstract][Full Text] [Related]  

  • 52. 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]  

  • 53. A Siamese Vision Transformer for Bearings Fault Diagnosis.
    He Q; Li S; Bai Q; Zhang A; Yang J; Shen M
    Micromachines (Basel); 2022 Sep; 13(10):. PubMed ID: 36296009
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Fault Diagnosis of Rotating Machinery Based on Improved Self-Supervised Learning Method and Very Few Labeled Samples.
    Wei M; Liu Y; Zhang T; Wang Z; Zhu J
    Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009734
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Intelligent Detection of a Planetary Gearbox Composite Fault Based on Adaptive Separation and Deep Learning.
    Sun GD; Wang YR; Sun CF; Jin Q
    Sensors (Basel); 2019 Nov; 19(23):. PubMed ID: 31795113
    [TBL] [Abstract][Full Text] [Related]  

  • 56. A Novel Bearing Fault Diagnosis Method Based on Few-Shot Transfer Learning across Different Datasets.
    Zhang Y; Li S; Zhang A; Li C; Qiu L
    Entropy (Basel); 2022 Sep; 24(9):. PubMed ID: 36141182
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Fault Diagnosis of Wind Turbine Gearbox Based on the Optimized LSTM Neural Network with Cosine Loss.
    Yin A; Yan Y; Zhang Z; Li C; Sánchez RV
    Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32325985
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Intelligent Fault Diagnosis for Chemical Processes Using Deep Learning Multimodel Fusion.
    Wang N; Yang F; Zhang R; Gao F
    IEEE Trans Cybern; 2022 Jul; 52(7):7121-7135. PubMed ID: 33378269
    [TBL] [Abstract][Full Text] [Related]  

  • 59. An adaptive fractional stochastic resonance method based on weighted correctional signal-to-noise ratio and its application in fault feature enhancement of wind turbine.
    Zeng X; Lu X; Liu Z; Jin Y
    ISA Trans; 2022 Jan; 120():18-32. PubMed ID: 33766454
    [TBL] [Abstract][Full Text] [Related]  

  • 60. An Intelligent Fault Diagnosis Method for Reciprocating Compressors Based on LMD and SDAE.
    Liu Y; Duan L; Yuan Z; Wang N; Zhao J
    Sensors (Basel); 2019 Feb; 19(5):. PubMed ID: 30823502
    [TBL] [Abstract][Full Text] [Related]  

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