Showing 81 - 100 results of 155 for search '"Case Western Reserve University"', query time: 0.08s Refine Results
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    Rolling-Element Bearing Fault Data Automatic Clustering Based on Wavelet and Deep Neural Network by Yanli Yang, Peiying Fu

    Published 2018-01-01
    “…The proposed method is tested with the bearing data provided by the Case Western Reserve University (CWRU) Bearing Data Center. The testing results show that the proposed method has good performance in automatic clustering of rolling-element bearings fault data.…”
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    Article
  3. 83
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    Deep Transfer Learning Method Based on 1D-CNN for Bearing Fault Diagnosis by Jun He, Xiang Li, Yong Chen, Danfeng Chen, Jing Guo, Yan Zhou

    Published 2021-01-01
    “…Finally, based on the bearing datasets of Case Western Reserve University and Jiangnan University, seven transfer fault diagnosis comparison experiments are carried out. …”
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    Article
  5. 85
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    Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning by Jing An, Ping Ai, Dakun Liu

    Published 2020-01-01
    “…Experimental results on the Case Western Reserve University bearing datasets confirm the superiority of the proposed method over many existing methods.…”
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    Article
  7. 87

    Deep Domain Adaptation Approach Using an Improved Parallel Residual Network for Cross-Domain Bearing Fault Diagnosis by Jiezhou Huang

    Published 2024-01-01
    “…Rolling bearing datasets from Case Western Reserve University (CWRU) and Jiangnan University (JNU) are used to validate the effectiveness of the presented method. …”
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    Article
  8. 88

    Rolling Bearing Fault Diagnosis Method Based on Multisynchrosqueezing S Transform and Faster Dictionary Learning by Guodong Sun, Ye Hu, Bo Wu, Hongyu Zhou

    Published 2021-01-01
    “…Experiments show that our method performs well on the rolling bearing dataset of Case Western Reserve University (CWRU) and the Society for Machinery Failure Prevention Technology (MFPT). …”
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    Article
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    Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance by Hao Luo, Xinyue Wang, Li Zhang

    Published 2025-01-01
    “…Experiments conducted across three imbalanced scenarios using the Case Western Reserve University (CWRU) and Paderborn University (PU) datasets demonstrate that NG-UDAN is effective in both single-source and mixed-source domain adaptation. …”
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    Article
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    Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis by Mohammed M. Farag

    Published 2025-01-01
    “…The framework is applied to two popular datasets – the Case Western Reserve University (CWRU) and Paderborn University (PU) bearing fault datasets. …”
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    Article
  16. 96

    MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning by Guangyuan Xu, Ruifeng Guo, Zhenyu Yin, Feiqing Zhang

    Published 2025-01-01
    “…The proposed method is experimentally verified on Case Western Reserve University, Jiangnan University, and laboratory datasets. …”
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    Article
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