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。

• XJTU-SY 滚动轴承加速寿命试验数据集解读(XJTU-SY rolling element bearing accelerated life test datasets: a tutorial) 2019 · 首发该数据集
• XJTU-SY Rolling Element Bearing Accelerated Life Test Datasets: A Tutorial 2019 · 首发该数据集
• A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings 2018 · 首发该数据集
• Physics-informed machine learning in prognostics and health management: a systematic literature review 2026 · 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
• Advancements in bearing remaining useful life prediction methods: a comprehensive review 2024 · 综述收录
• Deep transfer learning in machinery remaining useful life prediction: a systematic review 2024 · 综述收录
• Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016 2023 · 综述收录
• <scp>RUL</scp> Prediction of Rolling Bearings via Adaptive Multi‐Scale Feature Alignment and Semantic Fusion 2026 · 用于方法验证
• Prediction of Remaining Service Life for Rolling Bearings Using a CapsTCN‐Transformer Hybrid Model 2026 · 用于方法验证
• Physics‐Guided Swin‐KAN Transformer and Three‐Channel Log‐Energy Representation for Remaining Useful Life Prediction of Bearings 2026 · 用于方法验证
• Multi scale parallel frequency attention network for bearing fault diagnosis under severe noise 2026 · 用于方法验证
• ConvFormer with dynamic chunked self-attention for RUL prediction of rotating machinery 2026 · 用于方法验证
• TimeGPT for Mechanical System Degradation Assessment: A Large Time Series Model Approach 2026 · 用于方法验证
• TC-BiKAN: A domain-adaptive framework with Kolmogorov-Arnold networks for rolling bearing RUL prediction 2026 · 用于方法验证
• A mixture-of-experts prior-posterior fusion framework for predicting the remaining useful life of aerospace high-speed bearings 2026 · 用于方法验证
• E-BMAML: An enhanced Bayesian meta-learning framework with adaptive asymmetric calibration for uncertainty-aware few-shot industrial diagnostics 2026 · 用于方法验证
• UNFIT monitoring of roller bearing degradation: A new event-based concept for early defect detection 2026 · 用于方法验证
• A physics-guided multi-scale attention fusion network for bearing remaining useful life prediction 2026 · 用于方法验证
• Dilated attention ConvGRU for remaining useful life prediction of rolling bearings with uncertainty quantification 2026 · 用于方法验证

仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。