Wind turbine fault diagnosis dataset (FAST-NREL 5MW) 核心 · 已核验

atlas:wind-turbine-fault-diagnosis-dataset-fast-nrel-5mw

This repository contains the measurement signals used during the development and validation of a wind turbine fault diagnosis methodology.

The dataset includes six fault scenarios of a wind turbine benchmark. Each file fault_i.mat contains the time series of the available sensor measurements corresponding to fault condition i. A healthy operating condition is also provided.

The MATLAB live script read_Sensor_data.mlx is included for visualization and inspection of the sensor behavior and fault effects. They are provided to allow readers to understand the characteristics of the signals used to design and tune the diagnostic method.

The signals were generated using the wind turbine benchmark proposed by Odgaard, Stoustrup and Kinnaert (2013), based on the NREL 5-MW reference wind turbine implemented in FAST.

The FAST simulation model is not distributed. Only processed measurement signals required for diagnosis are provided.

Pérez-Pérez, E. J., Puig, V., Santos-Ruiz, I., Gúzman-Rabasa, J. A., & Valencia-Palomo, G. (2026). Wind turbine fault diagnosis using structural analysis and optimized-Rectangular GPR interval estimation. Control Engineering Practice, 172, 106940.  https://doi.org/10.1016/j.conengprac.2026.106940

落地页
https://zenodo.org/api/records/18718184
许可证
CC-BY-4.0 (判读置信:未知)
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
Zenodo
设备类型
wind_turbine
PHM 任务
fault_diagnosis

故障工况

description: 六种故障场景(FAST/NREL 5MW 基准仿真)fault_type: otherinduction: simulated_synthetic

传感器

sensor_type: otherobserved_property: othermounting_note: FAST 仿真基准可用测点(转速/桨距/功率/风速等)

运行工况

description: FAST/NREL 5MW 基准仿真:6 故障场景+健康运行condition_type: otheris_varying: True
关联论文(1 篇,候选区未经人工核验;candidate_citation = 共引启发式候选关联,非使用断言)
溯源(PROV,7 条)
source_citation: curation/dataset-shortlist-v0.yaml(mech_oam_hub#11)retrieved_on: 2026-07-08asserted_by: automated_harvestnote: 由清单条目初始化的最小候选卡
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about_field: tasks,equipment_types,fault_conditionssource_citation: facet-batch-02.yamlretrieved_on: 2026-07-08asserted_by: automated_extractionnote: 代理归纳刻面(依据:描述:FAST 仿真基准);候选区,晋升需人工核验
about_field: sensors,operating_conditionssource_citation: facet-batch-06.yamlretrieved_on: 2026-07-08asserted_by: automated_extractionnote: 代理归纳刻面(依据:Zenodo API 记录 18718184(2026-07-08 核));候选区,晋升需人工核验
about_field: source_citation: 人工核验:zfbin(抽查后委托批准 2026-07-09)retrieved_on: 2026-07-09asserted_by: human_curatorconfidence_level: human_verifiednote: 晋升核心区。首晋升批次 02:KLS-012 满卡(fill=1.00),七批策展逐批用户裁决 + 策展台抽查后委托执行;预检 evidence/KLS-016/02
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
about_field: license_idsource_citation: 人工核验:zfbin(三问拍板 2026-07-11)retrieved_on: 2026-07-11asserted_by: human_curatorconfidence_level: human_verifiednote: 人工改写。license 记法归一 cc-by-4.0 → CC-BY-4.0(SPDX 规范 id,ADR-25 清账①,2026-07-11 用户拍板;许可语义不变)