Multimodal dataset for wind turbine blade monitoring during lightning strikes 核心 · 已核验

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<b>Lightning strikes pose a significant threat to the structural integrity and operational performance of wind turbine blades. Due to the high probability of lightning strikes but the difficulty in capturing their dynamic data, obtaining comprehensive data on blades subjected to lightning strikes is challenging. This study presents a rare multimodal dataset for condition monitoring of multimodal wind turbine blades subjected to lightning strikes. The dataset collected from a wind farm in China. It includes vibration, load, and strain measurements from fiber optic load sensors and fiber optic accelerometer sensors. It provides real-time records of blade operational status and damage assessments after strikes. The dataset is intended to promote the development of predictive models for lightning strike detection and blade damage assessment, ultimately enhancing the monitoring, maintenance, and operational optimization of wind energy facilities. The dataset is publicly available for researchers to conduct in-depth studies in fields such as machine learning, condition monitoring, and fault prediction, contributing to the resilience and reliability of wind turbine operations.</b>

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落地页

https://dx.doi.org/10.6084/m9.figshare.28879679.v4

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

2025

发布方

figshare

设备类型

wind_turbine

PHM 任务

condition_monitoring

故障工况