UPATRAS Floating Wind Turbine Vibration Dataset for Damage Diagnosis under Varying Wind Conditions 核心 · 已核验

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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.

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落地页

https://data.mendeley.com/datasets/zmbjjg9kbj/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

2026

发布方

Mendeley Data

设备类型

wind_turbine

PHM 任务

fault_diagnosis health_state_assessment fault_detection

故障工况

传感器

运行工况