UPATRAS Floating Wind Turbine Vibration Dataset for Damage Diagnosis under Varying Wind Conditions 核心 · 已核验
doi:10.17632/zmbjjg9kbj.1
This repository contains vibration measurements acquired from a lab-scale Floating Wind Turbine (FWT) developed at the University of Patras, Stochastic Mechanical Systems and Automation (SMSA) Laboratory. The dataset is intended for research on vibration-based structural health monitoring, damage detection and damage diagnosis under varying operating conditions and related signal-processing, machine-learning and AI applications. The experimental campaign considers six structural states: one healthy state and five early-stage damage scenarios. The damage scenarios arise from three damage types: connection degradation between tower and floater, added mass simulating potential ice accumulation, and blade cracks. The FWT operates under nine operating conditions defined by the combination of three wind directions and three wind speeds. For each structural state and operating condition, ten repeated measurements are provided, resulting in a total of 540 vibration signals. All measurements are acquired using a single uniaxial accelerometer mounted on the upper part of the tower, with sampling frequency fs = 1024 Hz. Each signal contains N = 30 720 samples, corresponding to 30 s of vibration data and a frequency bandwidth of [0 − 512] Hz. Each measurement is provided in both CSV and MAT formats.
If you use this dataset in your work, please cite the following publication: https://doi.org/10.3390/s25041170
Further details on the data are available in the README.pdf file included in this dataset.
- 落地页
- https://data.mendeley.com/datasets/zmbjjg9kbj/1
- 许可证
- CC-BY-4.0 (判读置信:inferred)
- 国内可访问性
-
国内直连:可达 (2026-07-11 检测)
代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「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
- 2026
- 发布方
- Mendeley Data
- 设备类型
wind_turbine- PHM 任务
fault_diagnosishealth_state_assessmentfault_detection
故障工况
| fault_type: healthy_baseline |
| fault_type: blade_damage |
传感器
| sensor_type: accelerometer |
运行工况
| condition_type: environment |
溯源(PROV,8 条)
| source_url: https://api.datacite.org/dois/10.17632/zmbjjg9kbj.1source_citation: DataCite REST 反查(KLS-019,query=fault diagnosis)retrieved_on: 2026-07-10asserted_by: automated_harvestnote: 补量候选(281→300+),经全量人工复核入库;晋升需人工核验 |
| about_field: equipment_typessource_citation: graphrag 抽取自论文 doi:10.17632/zmbjjg9kbj.1(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: wind_turbine;候选区,晋升需人工核验(ADR-26) |
| about_field: fault_conditionssource_citation: graphrag 抽取自论文 doi:10.17632/zmbjjg9kbj.1(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: healthy_baseline, blade_damage;候选区,晋升需人工核验(ADR-26) |
| about_field: operating_conditionssource_citation: graphrag 抽取自论文 doi:10.17632/zmbjjg9kbj.1(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: environment;候选区,晋升需人工核验(ADR-26) |
| about_field: sensorssource_citation: graphrag 抽取自论文 doi:10.17632/zmbjjg9kbj.1(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: accelerometer;候选区,晋升需人工核验(ADR-26) |
| about_field: taskssource_citation: graphrag 抽取自论文 doi:10.17632/zmbjjg9kbj.1(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: fault_diagnosis, health_state_assessment, fault_detection;候选区,晋升需人工核验(ADR-26) |
| about_field: source_citation: 人工核验:zfbin(委托批准 2026-07-10)retrieved_on: 2026-07-10asserted_by: human_curatorconfidence_level: human_verifiednote: 晋升核心区。晋升批次 04:KLS-019 补量卡,逐卡逐断言对照自述核验(evidence/KLS-016/07) |
| about_field: china_accessibilitysource_citation: KLS-009 链接健康扫描(lychee 双通道)retrieved_on: 2026-07-11asserted_by: automated_harvestnote: 定期刷新标注,仅覆盖本字段;历史结果以最新扫描为准 |