基于振动的风电叶片运行故障特征提取

Jun Yan, Yuxiu Xu
{"title":"基于振动的风电叶片运行故障特征提取","authors":"Jun Yan, Yuxiu Xu","doi":"10.1109/ICCASE.2011.5997632","DOIUrl":null,"url":null,"abstract":"By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades' vibration signals can be used to classify the different working state of blades effectively. Experiments have also shown that this method is especially effective at working state monitoring and at fault diagnosis, and can achieve higher precision in these applications.","PeriodicalId":369749,"journal":{"name":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Operational Fault Feature Extraction of Blade Based on Vibration of Wind Turbine\",\"authors\":\"Jun Yan, Yuxiu Xu\",\"doi\":\"10.1109/ICCASE.2011.5997632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades' vibration signals can be used to classify the different working state of blades effectively. Experiments have also shown that this method is especially effective at working state monitoring and at fault diagnosis, and can achieve higher precision in these applications.\",\"PeriodicalId\":369749,\"journal\":{\"name\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Control, Automation and Systems Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCASE.2011.5997632\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Control, Automation and Systems Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCASE.2011.5997632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

通过对风力机采集数据的分析,计算振动信号的相关维数,并将其作为表征叶片工作状态的特征参数。计算结果表明,相关维数能有效地反映混沌吸引子的动态结构。因此,利用叶片振动信号的相关维数可以有效地对叶片的不同工作状态进行分类。实验结果表明,该方法在工作状态监测和故障诊断方面效果显著,具有较高的应用精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Operational Fault Feature Extraction of Blade Based on Vibration of Wind Turbine
By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades' vibration signals can be used to classify the different working state of blades effectively. Experiments have also shown that this method is especially effective at working state monitoring and at fault diagnosis, and can achieve higher precision in these applications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信