仅表示这篇论文与本数据集在文献网络中相邻, 不代表该论文确实使用了本数据集。

• Deep Learning and Few‐Shot Learning–Enabled Machine Health Monitoring for Rotating Machinery: A Critical Review of Vibration‐Based Fault Diagnosis, Prognostics, and Industrial Deployment 2026 · 综述收录
• Research Progress on Data-Driven Industrial Fault Diagnosis Methods 2025 · 综述收录
• Small data challenges for intelligent prognostics and health management: a review 2024 · 综述收录
• Feature learning for bearing prognostics: A comprehensive review of machine/deep learning methods, challenges, and opportunities 2024 · 综述收录
• Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal 2024 · 综述收录
• Recent deep learning models for diagnosis and health monitoring: A review of research works and future challenges 2023 · 综述收录
• Fault Prediction of Ball Bearings using Machine Learning: A Review 2023 · 综述收录
• A systematic review of rolling bearing fault diagnoses based on deep learning and transfer learning: Taxonomy, overview, application, open challenges, weaknesses and recommendations 2022 · 综述收录
• Machine Learning Based Bearing Fault Diagnosis Using the Case Western Reserve University Data: A Review 2021 · 综述收录
• Deep Learning Aided Data-Driven Fault Diagnosis of Rotatory Machine: A Comprehensive Review 2021 · 综述收录
• Bearing Fault Detection and Diagnosis Using Case Western Reserve University Dataset With Deep Learning Approaches: A Review 2020 · 综述收录
• Deep Learning Algorithms for Bearing Fault Diagnostics - A Review 2019 · 综述收录
• Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study 2015 · 综述收录
• Adaptive Dual‐Attention Learning Frame for Bearing Fault Diagnosis 2026 · 用于方法验证
• Reliable Intelligent Diagnostics With Uncertainty Quantification for Mechanical System Condition Assessment 2026 · 用于方法验证
• A Learnable FIR and DPEE‐Based Selective SSM–Conv Framework for Cross‐Condition Bearing Fault Diagnosis 2026 · 用于方法验证
• Real-time intelligent bearing fault diagnosis based on dual path three-folded residual network 2026 · 用于方法验证
• IMFD-Net with Hybrid Map Learning for Bearing Fault Diagnosis Under Diverse Conditions 2026 · 用于方法验证
• A latent-dynamics self-supervised framework for limited-label fault diagnosis in cyclostationary vibration measurements 2026 · 用于方法验证
• On simple baselines for domain shift in condition monitoring: A case study in bearing fault identification 2026 · 使用该数据集

仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。