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。

• XAI-PdMNet-Bench: an explainable generative AI framework for leakage-safe predictive maintenance in industry 5.0 manufacturing 2026 · 用于方法验证
• A Physics-Informed LSTM Approach for Cross-Domain Tool Wear Prediction Across Tool Individuals 2026 · 用于迁移/跨工况
• A Transformer-GAN Model for Tool Wear Prediction Based on Time-Series Data 2026 · 用于方法验证
• Autoencoders for learning latent information of cutting tool health 2026 · 用于方法验证
• Remaining Useful Life Prediction of End Mills Using DCNN-McBiLSTM-LRSA with Multi-Source Sensory Signals 2026 · 用于方法验证
• A CNC Machine Tool Wear Prediction Model Integrating Deep Reinforcement Learning and Edge Data Processing 2026 · 用于方法验证
• Remaining Useful Life Prediction of End Mills Using DCNN-McBiLSTM-LRSA with Multi-Source Sensory Signals 2026 · 用于方法验证
• Tool Wear Prediction in Complex Machining Processes: A Hybrid Residual-Compensated Deep Learning Framework 2026 · 用于方法验证
• Tool Wear Prediction Under Varying Cutting Conditions: A Few-Shot Warm-Start Framework Based on Model-Agnostic Meta-Learning 2026 · 用于方法验证
• PHM Services Based on Cyber–Physical Machine Tool System 2026 · 用于方法验证
• Automated CNC Tool Wear Detection System Using Multi-Domain Signal Processing and Machine Learning 2026 · 用于方法验证
• Automated CNC Tool Wear Detection System Using Multi-Domain Signal Processing and Machine Learning 2026 · 用于方法验证
• Comparative Analysis of Time, Frequency, and Wavelet Features for Tool Condition Monitoring Using Machine Learning under Cross-Tool Validation 2026 · 用于方法验证
• Wavelet-based multi-branch deep learning for tool wear monitoring with physics-informed label construction 2026 · 候选引用(未核验)
• Tool wear prediction based on multi-scale dilated convolution long short-term memory network with channel-spatial attention 2026 · 候选引用(未核验)
• A spatio-temporal feature fusion network based on deep learning for collaborative prediction of tool wear and machining precision 2026 · 候选引用(未核验)
• Multi-task hierarchical domain adaptation multi-expert attention network for cross-domain tool wear monitoring and remaining useful life estimation 2026 · 候选引用(未核验)
• Kalman-enhanced artificial intelligence in machining: A systematic review 2026 · 候选引用(未核验)
• Physics-guided safe collaboration: an uncertainty-gated heterogeneous semi-supervised regression framework for tool wear prediction 2026 · 候选引用(未核验)
• ToolMamba: a physics-informed framework for interpretable tool condition monitoring under various machining conditions 2026 · 候选引用(未核验)

仅列前 20 篇(首发/综述优先,按年份倒序);全量见 API。