{"title":"Emergency fault diagnosis for wind turbine nacelle","authors":"Yu Pang, L. Jia, Zhan Liu, Q. Gao","doi":"10.1109/DDCLS.2017.8068069","DOIUrl":null,"url":null,"abstract":"Many sets of wind turbines of the wind farm in Shan Xi province run above the rated wind speed, especially in the condition of wind speed 17m/s or above, wind turbine nacelle occurs vibration in the vertical direction of transmission chain which is characterized emergency, intermittent, accidental, and distinctive. Moreover, vibration cycle is not obvious and vibration strength is large. Severe vibration does harm to wind turbine that then will be able to lead wind turbine halt. According to this phenomenon, a method of emergency fault diagnosis for wind turbine nacelle based on empirical mode decomposition (EMD) is presented in this paper to discriminate a variety of factors carefully that have led to excessive vibration. In particular, the results are shown in this paper that strong tower shadow effect may cause excessive vibration of wind turbine nacelle, and then gives rise to shut down. In the meantime, curve theory analysis of the blade's aerodynamic characteristics is deduced in this paper. It demonstrates that the proposed method EMD works well in the face of fault diagnosis for wind turbine nacelle with a better overall performance.","PeriodicalId":419114,"journal":{"name":"2017 6th Data Driven Control and Learning Systems (DDCLS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th Data Driven Control and Learning Systems (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS.2017.8068069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Many sets of wind turbines of the wind farm in Shan Xi province run above the rated wind speed, especially in the condition of wind speed 17m/s or above, wind turbine nacelle occurs vibration in the vertical direction of transmission chain which is characterized emergency, intermittent, accidental, and distinctive. Moreover, vibration cycle is not obvious and vibration strength is large. Severe vibration does harm to wind turbine that then will be able to lead wind turbine halt. According to this phenomenon, a method of emergency fault diagnosis for wind turbine nacelle based on empirical mode decomposition (EMD) is presented in this paper to discriminate a variety of factors carefully that have led to excessive vibration. In particular, the results are shown in this paper that strong tower shadow effect may cause excessive vibration of wind turbine nacelle, and then gives rise to shut down. In the meantime, curve theory analysis of the blade's aerodynamic characteristics is deduced in this paper. It demonstrates that the proposed method EMD works well in the face of fault diagnosis for wind turbine nacelle with a better overall performance.