Dataset concerning the vibration signals from wind turbines in northern Sweden

In the manuscript, we investigate condition monitoring methods based on unsupervised dictionary learning. The dataset includes the raw time-domain vibration signals from six turbines within the same wind farm (near geographical location). All the wind turbines are of the same type and possess a three-stage gearbox. All measurement data corresponds to the axial direction of an accelerometer mounted on the housing of the output shaft bearing of each turbine. The sampling rate is 12.8 kilosamples/second and each signal segment is 1.28 seconds long (16384 samples). There are six files, which contains the vibration data from each of the six wind turbines. Within each file, each row corresponds to a different measurement. Furthermore, the first column represents the time expressed in years since the vibration data started to be recorded. The second column is the speed expressed in cycles per minute. The remaining columns are the vibration signal time series expressed in Gs. The dataset was originally published in DiVA and moved to SND in 2024.本手稿针对基于无监督字典学习的状态监测方法开展研究。 本数据集包含同一风电场（地理位置相近）内6台风力发电机组的原始时域振动信号。所有风力发电机组均为同型号配置，且搭载三级齿轮箱。所有测量数据均来自安装于每台机组输出轴轴承座上的加速度计轴向采集信号。采样率为12.8千采样点/秒，单段信号时长为1.28秒（对应16384个采样点）。 本数据集共包含6个数据文件，分别对应6台风力发电机组的振动数据。每个文件中，每一行代表一次独立的测量结果。其中，第一列为自振动数据开始记录以来的时长（单位：年）；第二列为机组转速（单位：转/分钟）；其余列均为以Gs表示的振动信号时域序列。 本数据集最初发布于DiVA平台，并于2024年迁移至SND平台。

搜集汇总

背景与挑战

背景概述

该数据集包含瑞典北部同一风电场六台相同类型风力涡轮机的振动信号数据，用于基于无监督字典学习的条件监测研究。数据采集自输出轴轴承的轴向加速度计，采样率为12.8 kHz，每个信号段长度为1.28秒，并以CSV文件格式提供，包括时间、速度和振动信号时间序列。数据集为开放访问，适用于工业电子和机械工程领域的研究。