摘要
风电塔筒是风电机组重要支撑结构,其垂直度对机组安全及稳定性有重要影响,塔筒受自然和人为因素的长期影响会出现表面损伤、结构不均匀等现象,塔筒的传统监测方法会产生异常误差而导致测量结果失真。对此,本文采用稳健估计理论分析风电塔筒垂直度,结合最小二乘法拟合塔筒截面测量值的圆心及半径,通过Huber迭代权函数,逐步消除测量值序列存在的粗差、偶然误差等异常测点的影响,并采用实例进行验证。结果表明:稳健最小二乘法拟合风电塔筒垂直度具有较强的抗差能力,可有效避免粗差、偶然误差等异常测量值的影响,提高了拟合参数和垂直度分析的可靠性,易于编程实现,具有较强的实用价值,该方法可为风力发电塔及类似高耸塔筒的垂直度监测分析提供参考。
Tower of wind turbine generator is used as bracing structure of generator set,and its perpendicularity has strong sensitivity to its safety and stability.Affected by long-term natural and human factors,the tower suffurs surface damage and structural inhomogeneity.As a result,the conventional monitoring methods will generate abnormal errors,which directly leads to distortion of the measurement results.To solve this problem,the authors use the robust estimation theory to carry out perpendicularity analysis on wind power towers for the first time.Moreover,combined with least square method,the center and radius of the measured value of the section of the tower tube are fitted,and by using Huber selecting weight iteration method,it will gradually eliminate the influence of abnormal measuring points such as gross errors and accidental errors in the measured value series.Finally,this method is verified by an instance.The results show that,the robust least-square circle fitting has ability to resist errors,which can effectively avoid the influence of abnormal measurement values such as gross errors and accidental errors,and improve the reliability of fitting parameters and perpendicularity analysis.This method has the advantages of clear logic,simple programming method and practical value.The research results provide a reference for the perpendicularity analysis of the tower of wind turbine generator and similar towers.
作者
程帅
米珂
李晓博
舒进
陈仓
兰昊
汪俊波
CHENG Shuai;MI Ke;LI Xiaobo;SHU Jin;CHEN Cang;LAN Hao;WANG Junbo(Xi’an Thermal Power Research Institute Co.,Ltd.,Xi’an 710054,China)
出处
《热力发电》
CAS
CSCD
北大核心
2021年第9期152-159,共8页
Thermal Power Generation
基金
中国华能集团有限公司总部科技项目(HNKJ18-H34)。
关键词
稳健估计
最小二乘法
风电塔筒
垂直度
误差
迭代权函数
robust estimation
least-square method
wind turbine tower
perpendicularity
error
iterative weight function