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{"title":"Adaptive Optimal Resonance Fault Feature Enhancement for Wind Turbine Based on Frequency Search and Uncertainty Analysis","authors":"Jian Dang, Yile Wang, Haolin Yin, Ji Li, Rong Jia, Peihang Li","doi":"10.1002/tee.24168","DOIUrl":null,"url":null,"abstract":"<p>The wind turbine fault feature has strong uncertainty due to various factors such as wind speed and equipment parameters. Based on the analysis of the vibration characteristics of wind turbines with unknown prior conditions, this paper conducts research on the enhancement method of fault features. First, analyzing the change in fault features caused by the change in operating conditions to lay the foundation for subsequent research; Second, for the uncertainty of wind turbine fault feature frequency, searching for fault features by constructing the energy in each spectral interval, then use signal noise optimal resonance to transfer noise energy to low frequency fault features to achieve the purpose of adaptive optimal resonance enhancement of fault feature; Finally, validation of the proposed method by simulation experiments and fault signals of actual wind turbine rolling bearings. The case shows that the proposed algorithm can effectively realize the uncertain fault feature of wind turbines search and enhancement. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"19 12","pages":"2044-2061"},"PeriodicalIF":1.0000,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEJ Transactions on Electrical and Electronic Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/tee.24168","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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Abstract
The wind turbine fault feature has strong uncertainty due to various factors such as wind speed and equipment parameters. Based on the analysis of the vibration characteristics of wind turbines with unknown prior conditions, this paper conducts research on the enhancement method of fault features. First, analyzing the change in fault features caused by the change in operating conditions to lay the foundation for subsequent research; Second, for the uncertainty of wind turbine fault feature frequency, searching for fault features by constructing the energy in each spectral interval, then use signal noise optimal resonance to transfer noise energy to low frequency fault features to achieve the purpose of adaptive optimal resonance enhancement of fault feature; Finally, validation of the proposed method by simulation experiments and fault signals of actual wind turbine rolling bearings. The case shows that the proposed algorithm can effectively realize the uncertain fault feature of wind turbines search and enhancement. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
基于频率搜索和不确定性分析的风力涡轮机自适应优化共振故障特征增强技术
受风速、设备参数等多种因素的影响,风力发电机故障特征具有很强的不确定性。本文在分析先验条件未知的风电机组振动特性的基础上,对故障特征的增强方法进行了研究。首先,分析运行工况变化引起的故障特征变化,为后续研究奠定基础;其次,针对风电机组故障特征频率的不确定性,通过构建各频谱区间的能量来搜索故障特征,然后利用信号噪声最优共振将噪声能量转移到低频故障特征上,达到自适应最优共振增强故障特征的目的;最后,通过仿真实验和实际风电机组滚动轴承的故障信号对提出的方法进行验证。结果表明,提出的算法能有效实现风力发电机不确定故障特征的搜索和增强。© 2024 日本电气工程师学会和 Wiley Periodicals LLC。
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