University of Ottawa Ball-bearing Vibration and Acoustic Fault Data under Constant Load and Speed Conditions (UODS-VAFDC) 核心 · 已核验
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The dataset provides signals gathered from an accelerometer, a microphone, a load cell, and a hall effect sensor operating under stable loads and speeds. This dataset provides a platform to assess the effectiveness of fault diagnosis techniques under constant conditions. Using this data, various methods can be tested and evaluated for their efficiency in detecting faults. Moreover, the dataset holds great potential in facilitating the application and refinement of deep learning methods. With this resource, researchers can conduct thorough testing to enhance the accuracy and reliability of machine learning methods. The first column provides accelerometer data, the second column is acoustic data, the third column is motor speed, and the fourth column is the load.
Each dataset is collected under a constant speed and load. A total of 20 bearings are tested, where each bearing has three associated datasets for three different conditions: healthy, fault developing, and faulty. Therefore, a total of 60 datasets are included.
In all cases, the data is sampled at 42,000 Hz, the sampling duration is 10s, and the nominal rotational speed of the bearing is 1,750 RPM. All data collected for healthy bearings, and bearings with inner, outer, or cage faults are collected under a nominal constant load of 400 N. Ball fault data is collected under no load. The datasets are labelled as {Letter}-{Number}-(Number}, where:
• The letter represents the bearing’s final condition: H = healthy, I = inner race fault, O = outer race fault, B = ball fault, C = cage fault.
• The first number identifies the bearing that is tested.
• The second number represents the bearing’s health condition: 0 = healthy, 1 = fault developing, 2 = faulty.
• Examples of inner race fault dataset labelling:
o I-2-1 means an inner race fault for bearing 2 with a fault developing.
o I-2-2 means an inner race fault for bearing 2 that is faulty.
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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://dx.doi.org/10.17632/y2px5tg92h.1
- 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
- 别名
- UODS-VAFDC
- 设备类型
rolling_bearing- PHM 任务
fault_diagnosis
传感器
| sensor_type: accelerometerobserved_property: vibration_acceleration |
| sensor_type: microphoneobserved_property: acoustic_pressure |
关联论文(6 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。
- Vibration-based bearing fault diagnosis in noisy conditions using matrix pencil mean frequency and multilayer perceptron neural networks 2026 · 用于方法验证
- Adaptive Resonance Demodulation for Bearing Fault Diagnosis via Spectral Trend Reconstruction and Weighted Logarithmic Energy Ratio 2026 · 用于方法验证
- Learning the Language of Vibration: A Self-Supervised Transformer Foundation Model for PHM 2026 · 候选引用(未核验)
- Ottawa Bearing Dataset with Noise 2025 · 用于方法验证
- Ottawa Bearing Dataset with Noise 2025 · 用于方法验证
- University of Ottawa Ball-Bearing Vibration and Acoustic Fault Data Under Constant Load and Speed Conditions (UODS-VAFDC): Experimental Setup 2023 · 候选引用(未核验)
溯源(9 条)
| 日期: 2026-07-08 |
| 来源链接: https://api.datacite.org/dois/10.17632/y2px5tg92h.1 日期: 2026-07-08 |
| 日期: 2026-07-08 |
| 日期: 2026-07-10 |
| 日期: 2026-07-11 |
| 日期: 2026-07-11 |
| 日期: 2026-07-21 |
| 日期: 2026-07-25 |
| 日期: 2026-07-31 |