SEU Gearbox Dataset (Southeast University Mechanical-datasets) 核心 · 已核验
mxdsapffh9nr8a03
东南大学 DDS 传动系统模拟器采集的齿轮箱+轴承双子集,跨工况迁移学习高引基准(Shao et al.)
本卡描述如含来自官方页的原文片段,其版权归原作者,不在本站 CC-BY 4.0 许可范围(见关于与许可)。
- 落地页
- https://github.com/cathysiyu/Mechanical-datasets
- 国内可访问性
-
国内直连:可达 (2026-07-11 检测)
非直连:可达 (2026-07-11 检测)
「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。 - 发布年份
- 2019
- 设备类型
gearboxrolling_bearing- PHM 任务
fault_diagnosisdomain_adaptation
故障工况
| fault_type: healthy_baseline |
| description: 齿根裂纹fault_type: gear_tooth_crack |
| description: 断齿/缺齿fault_type: gear_tooth_breakage |
| description: 齿面磨损fault_type: gear_wear |
| fault_type: bearing_inner_race_fault |
| fault_type: bearing_outer_race_fault |
| fault_type: bearing_rolling_element_fault |
| fault_type: compound_fault |
传感器
| sensor_type: accelerometerobserved_property: vibration_accelerationchannel_count: 8mounting_note: 电机/行星齿轮箱/平行齿轮箱 x-y-z 振动+扭矩共 8 通道(DDS 台架) |
| sensor_type: torque_transducerobserved_property: torque |
运行工况
| description: 两种转速-负载组合(20Hz-0V/30Hz-2V)condition_type: other |
关联论文(43 篇)
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。
- An Interval Belief Rule Base Method with Attention Enhancement for Bearing Fault Diagnosis Under Variable Operating Conditions 2026 · 用于方法验证
- Lightweight Gearbox Fault Diagnosis Under High Noise Based on Improved Multi-Scale Depthwise Separable Convolution and Efficient Channel Attention 2026 · 用于方法验证
- A GCU-SAM Enhanced Transformer for Fault Diagnosis of Rotating Machinery 2026 · 用于方法验证
- Industrial robot transmission components cross-machines fault diagnosis via fault intrinsic representation and channel self-healing under sensor failure 2026 · 候选引用(未核验)
- A multi-level bidirectional cross-attention framework for multi-sensor fault diagnosis of rotating machinery 2026 · 候选引用(未核验)
- Physical-Causal Guided Adaptive Time-Frequency and Hypergraph Co-evolutionary Modeling Method for Industrial Equipment Monitoring 2026 · 候选引用(未核验)
- Prior-Guided Topological Domain Adaptation Network for Cross-Condition Fault Diagnosis Using Multi-Sensor Vibration Measurements 2026 · 候选引用(未核验)
- Two-Stage Harmonic Optimization-Gram Based on Spectral Amplitude Modulation for Rolling Bearing Fault Diagnosis 2026 · 候选引用(未核验)
- A PI-Dual-STGCN Fault Diagnosis Model Based on the SHAP-LLM Joint Explanation Framework 2026 · 候选引用(未核验)
- A Dual-Source Evidence–Driven Semi-Supervised Belief Rule Base for Fault Diagnosis 2026 · 候选引用(未核验)
- Let the Model Choose Its Own Frequency: An Adaptive Frequency-Aware Inverted Transformer for Noise-Robust Gearbox Fault Diagnosis 2026 · 候选引用(未核验)
- Learning the Language of Vibration: A Self-Supervised Transformer Foundation Model for PHM 2026 · 候选引用(未核验)
- Rolling bearings fault diagnosis using a one-dimensional vision transformer with multi-scale residual convolution 2025 · 用于方法验证
- An Optimized SFE-FuseNet for Gearbox Bearing Fault Diagnosis Under Limited Training Samples 2025 · 用于方法验证
- Label-Noise-Resistant Time-Series Classification With Self-Supervised Label Correction 2025 · 用于方法验证
- Intelligent Fault Classification Exploration Inspired by Suprathreshold Stochastic Resonance 2025 · 用于方法验证
- Intelligent fault diagnosis technique for rotating machinery based on parameter-optimised variational mode decomposition and improved bidirectional gated recurrent unit 2025 · 用于方法验证
- YConvFormer: A Lightweight and Robust Transformer for Gearbox Fault Diagnosis with Time–Frequency Fusion 2025 · 用于方法验证
- FreFilterTST: a dynamic channel graph sparsification approach to multivariate time series anomaly detection with frequency-domain restoration 2025 · 候选引用(未核验)
- Fault Diagnosis of Rotating Machines Based on Combination of One‐Dimensional Convolutional Neural Network and Long Short‐Term Memory in Variable Working Conditions 2025 · 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。
溯源(9 条)
| 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-10 |
| 日期: 2026-07-11 |
| 日期: 2026-07-14 |
| 日期: 2026-07-25 |
| 日期: 2026-07-26 |
| 日期: 2026-07-26 |