电力建设Issue(8)：125-129,5.DOI:10.3969/j.issn.1000-7229.2014.08.022
基于相对主元分析的风电机组塔架振动状态监测与故障诊断
Tower Vibration Fault Diagnosis and Monitoring for Wind Turbines Based on RPCA
摘要
Abstract
Vibration signal is one kind of important variables in supervisory control and data acquisition system (SCADA)for wind turbines.Based on SCADA data and wind turbine operating theory,this paper firstly analyzed the factors that had great influence on tower vibration.Then relative principal components analysis (RPCA)was used to model the tower vibration during the normal work of wind turbine combined with the SCADA data of a wind turbine between March and May 2011.Two statistic variables Hotelling T2 and SPE (squared prediction error)were calculated.The RPCA tower vibration model then was used to accurately detect the blade angle asymmetry fault,which could prove the effectiveness of this method.关键词
风电机组/塔架振动/状态监测/相对主元分析(RPCA)/数据采集与监控系统(SCADA)/建模Key words
wind turbines/tower vibration/condition monitoring/relative principal component analysis (RPCA)/supervisory control and data acquisition system(SCADA)/modeling分类
信息技术与安全科学引用本文复制引用
周进,房宁,郭鹏..基于相对主元分析的风电机组塔架振动状态监测与故障诊断[J].电力建设,2014,(8):125-129,5.基金项目
国家自然科学基金（51207049）；新能源电力系统国家重点实验室开放基金项目（LAPS13011）。 （）
