自注意力优化密度聚类的风机数据清洗方法  

Transformer-Optimized DBSCAN for Wind Turbine Data Cleaning

作　　者：张茹顶 张铖 潘钱宇 李少帅 孟井煜枫 吴博阳 ZHANG Ruding;ZHANG Cheng;PAN Qianyu;LI Shaoshuai;MENG Jingyufeng;WU Boyang(Windey Energy Technology Group Co.,Ltd.,Hangzhou 310000,China)

机构地区：[1]运达能源科技集团股份有限公司,杭州310000

出　　处：《微特电机》2025年第4期34-38,共5页Small & Special Electrical Machines

摘　　要：针对风电机组监控与数据采集系统常受多种因素影响,导致数据异常问题,提出一种基于自注意力编码器改进的密度聚类模型方法,结合自注意力编码器的特征提取能力和密度聚类的空间特性,通过引入相对位置编码和优化多头注意力机制,提升对监控与数据采集系统异常数据识别能力。实验结果表明,所提方法的数据清洗效果和模型精度与传统方法相比更优,其中异常数据剔除率达到26.58%,并且在拟合风速-功率曲线时,平均绝对误差、均方根误差最低,决定系数最高。清洗后的监控与数据采集系统数据应用于机组故障诊断,将风电机组故障识别准确性提高到了92%以上、故障预警及时性提前了20%,故障类型分类精度提高了30%。该方法不仅提高了风电机组的运行效率和可靠性,还为风电场的运行管理和决策提供了较为可靠的数据支持。The supervisory control and data acquisition(SCADA)system for wind turbines is often affected by various factors,leading to data anomalies.This article proposes a A method for improving the density-based spatial clustering of applications with noise(DBSCAN)clustering model based on Transformer autoencoder was proposed.By combining the feature extraction ability of Transformer and the density clustering characteristics of DBSCAN,relative position encoding and optimized multi head attention mechanism were introduced to enhance the recognition ability of SCADA abnormal data.The experiment shows that compared with traditional methods,the data cleaning effect and model accuracy were better.The abnormal data removal rate of this method reached 26.58% and when fitting the wind speed power curve,MAE and RMSE were the lowest and R^(2) was the highest.The cleaned SCADA data used for unit fault diagnosis can significantly improve the accuracy of wind turbine fault identification over 92%,the timeliness of fault warning 20% in advance,and the accuracy of fault type classification 30% improvement.This method not only improved the operational efficiency and reliability of wind turbines,but also provided more reliable data support for the operation management and decision-making of wind farms.

关 键 词：自注意力编码器 密度聚类算法 数据清洗 监控与数据采集系统 风电机组 

分 类 号：TM315[电气工程—电机]