可再生能源2017，Vol.35Issue(4)：508-514,7.
主成分-灰色关联分析方法的风电机组齿轮箱故障诊断
PCA and GRA method in the diagnosis of wind turbine gearbox failure
摘要
Abstract
In view of the difficulties in failure diagnosis of wind turbine,which is because of equipment varying duty,a PCA (principal component analysis)-GRA (grey relational analysis)method is proposed to deal with it.Utilizing the method of order resampling,the nonlinearity data bad influence can be eliminated;in consideration of analytic error by signal energy fluctuation,nondimensional parameters are regarded as characteristics of the fault diagnosis data;the weight of every characteristic parameter can be given by PCA-GRA,which not only promote the relationship between failure mode and analyze data,but also improve the accuracy of fault diagnosis.The test and actual analysis results shown that the improved method could diagnosis wind turbine gearbox failure effectively,which has a good practical significance.关键词
风电齿轮箱/阶比重采样/无量纲参数/主成分分析/灰色关联分析Key words
wind turbine/order resampling/non-dimensional parameter/principal component analysis/grey relational analysis分类
能源科技引用本文复制引用
顾煜炯,贾子文,尹传涛,曹力,雷启龙..主成分-灰色关联分析方法的风电机组齿轮箱故障诊断[J].可再生能源,2017,35(4):508-514,7.基金项目
神华集团科技创新项目(SHJT-12-24) （SHJT-12-24）
中央高校基本科研业务专项基金(2016XS27). （2016XS27）
