SCADA dataset of a 2 MW SIEMENS wind turbine drivetrain located at a wind farm on the Baltic Sea coast in northern Poland 核心 · 已核验

doi:10.17632/3sys4562ny.1

This dataset contains Supervisory Control and Data Acquisition (SCADA) measurements from a 2 MW Siemens wind turbine drivetrain located at a wind farm on the Baltic Sea coast in northern Poland. The data were extracted to investigate whether early indicators of a gearbox fault could be detected using data-driven analysis.

The monitoring period spans 30 days, from November 1, 2012 (00:00) to November 30, 2012 (23:50). Operational parameters were recorded at 10-minute intervals, resulting in 4,320 time-series samples for each parameter.

The dataset includes twelve process parameters describing the turbine’s operational condition, grouped into rotational dynamics, electrical power generation, and thermal conditions. Rotational parameters include wind speed, rotor speed, and generator speed. Electrical parameters include active power, generated power, reactive power, reactive power delivered, generator voltage, and generator current, representing the turbine’s power generation and load conditions. Thermal parameters include gearbox bearing temperature and two generator temperature sensors, indicating the thermal state of key components.

During operation, a gearbox bearing failure occurred and was recorded on November 9, 2012 at 13:00 (sample 1232). The dataset therefore contains both normal operational data and data preceding the fault event. In the related study, generator speed and gearbox bearing temperature were used to validate a stationarity-based anomaly detection method.

SCADA measurements represent 10-minute averaged values, typical for wind turbine monitoring systems. The dataset contains no missing or corrupted values, making it suitable for research on condition monitoring, anomaly detection, time-series analysis, and predictive maintenance of wind turbines.

Related published papers:

1) P.B. Dao, W.J. Staszewski, T. Barszcz, and T. Uhl, “Condition monitoring and fault detection in wind turbines based on cointegration analysis of SCADA data,” Renewable E

落地页

https://data.mendeley.com/datasets/3sys4562ny/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 gearbox rolling_bearing

PHM 任务

fault_detection anomaly_detection condition_monitoring

运行工况