HUST bearing: a practical dataset for ball bearing fault diagnosis 核心 · 已核验
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In this work, we introduce a practical dataset named HUST bearing, that provides a large set of vibration data on different ball bearings. This dataset contains 99 raw vibration data of 6 types of defects (inner crack, outer crack, ball crack, and their 2-combinations) on 5 types of bearing at 3 working conditions with the sample rate of 51,200 samples per second.
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- 落地页
- https://dx.doi.org/10.17632/cbv7jyx4p9.3
- 许可证
- CC-BY-4.0 (置信:verified_official)
- 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
- 2023
- 发布方
- Mendeley Data
- 别名
- HUST bearing
- 设备类型
rolling_bearing- PHM 任务
fault_diagnosis
故障工况
| fault_type: bearing_inner_race_fault |
| fault_type: bearing_outer_race_fault |
| fault_type: bearing_rolling_element_fault |
| description: 双故障组合fault_type: compound_fault |
传感器
| sensor_type: accelerometerobserved_property: vibration_accelerationsampling_rate_hz: 51200.0 |
运行工况
| description: 3 种工况 × 5 种轴承型号condition_type: other |
关联论文(4 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。
- A Novel Approach for Motor Bearing Fault Detection Using EMD-Based Denoising and Detrended Fluctuation Analysis & LSTM Multimodal Hybrid Features with K-Means Clustering 2026 · 使用该数据集
- Physics-Aware Lightweight Artificial Intelligence (AI) for Bearing Fault Diagnosis in Industry 4.0 Predictive Maintenance 2026 · 候选引用(未核验)
- Enhanced Fault Classification in Bearings: A Multi-Domain Feature Extraction Approach with LSTM-Attention and LASSO 2024 · 使用该数据集
- Early Detection of Ball Bearing Faults Using the Decision Tree Method 2024 · 使用该数据集
溯源(12 条)
| 日期: 2026-07-08 |
| 来源链接: https://api.datacite.org/dois/10.17632/cbv7jyx4p9.3 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-09 |
| 日期: 2026-07-11 |
| 日期: 2026-07-11 |
| 日期: 2026-07-21 |
| 日期: 2026-07-25 |
| 日期: 2026-07-26 |
| 日期: 2026-07-31 |