基于残差网络的风电机组基础健康监测数据修复研究

魏焕卫; 宋志鑫; 雷树立; 惠俊梅; 郑晓

doi:10.19912/j.0254-0096.tynxb.2022-1884

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (4) : 143-150. DOI: 10.19912/j.0254-0096.tynxb.2022-1884

基于残差网络的风电机组基础健康监测数据修复研究

魏焕卫^1~3, 宋志鑫^1,2, 雷树立^1,2, 惠俊梅⁴, 郑晓^1~3

作者信息 +

RESEARCH ON HEALTH MONITORING DATA RESTORATION OF WIND TURBINE FOUNDATION BASED ON RESIDUAL NETWORK

Wei Huanwei^1~3, Song Zhixin^1,2, Lei Shuli^1,2, Hui Junmei⁴, Zheng Xiao^1~3

Author information +

文章历史 +

摘要

为精准有效地修复连续性异常数据,提出一种基于残差块优化卷积神经网络的残差网络数据修复模型。以乳山风电场的风电机组基础健康监测数据为例对模型进行工程验证。同时选取具有修复功能的多种模型对实际异常数据进行修复验证,并对所有模型的性能以及自身的修复精度进行对比分析。结果表明：ResNet模型避免了FCN以及CNN模型存在的缺陷,提高了数据修复的精度;ResNet模型适用于缺失或异常比例低于30%的数据修复;ResNet模型修复实例的结果符合数据变化趋势,能较好吻合监测数据的原始曲线。

Abstract

To accurately and effectively repair the abnormal data of the continuous monitoring dataset, a residual network data repairing （ResNet） model was proposed based on residual block optimized convolutional neural network in this paper. The engineering validation of the proposed ResNet model was carried out by using the health monitoring data of the foundation of the onshore wind turbine at Rushan Wind Farm. Some models with repair functions were also selected to repair the abnormal data of the monitoring dataset. According to the results of the repaired monitoring dataset, the comparative analysis was conducted on the repair performance and accuracy of these models. The results reveals that comparing with FCN and CNN model, ResNet model exhibits a rather high accuracy of abnormal data repair; the ResNet model is more suitable for repairing datasets where the ratio of missing or abnormal data is less than 30%; the repaired results based on the ResNet model can fit better to the original curve of the continuous monitoring data,which shows a good agreement with the monitored trend.

导出引用

魏焕卫, 宋志鑫, 雷树立, 惠俊梅, 郑晓. 基于残差网络的风电机组基础健康监测数据修复研究[J]. 太阳能学报. 2024, 45(4): 143-150 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1884

Wei Huanwei, Song Zhixin, Lei Shuli, Hui Junmei, Zheng Xiao. RESEARCH ON HEALTH MONITORING DATA RESTORATION OF WIND TURBINE FOUNDATION BASED ON RESIDUAL NETWORK[J]. Acta Energiae Solaris Sinica. 2024, 45(4): 143-150 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1884

中图分类号： TU476 TP183

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