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山东大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (4): 96-102.doi: 10.6040/j.issn.1672-3961.0.2016.394

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基于阶次分析的风电机组在线模态参数识别与故障诊断

李静立1,王谦1,张军2,李磊磊1   

  1. 1. 甘肃新泉风力发电有限公司, 甘肃 兰州 730070;2. 江苏省电力公司经济技术研究院, 江苏 南京 210008
  • 收稿日期:2016-10-26 出版日期:2017-08-20 发布日期:2016-10-26
  • 作者简介:李静立(1971— ),男,山东德州人,高级工程师,硕士,主要研究方向为新能源运行管理与风电并网技术研究.E-mail:ljlcn@vip.163.com

Online modal parameter identification and fault diagnosis of wind turbines based on order analysis

LI Jingli1, WANG Qian1, ZHANG Jun2, LI Leilei1   

  1. 1. Gansu Xinquan Wind Power Company Limited, Lanzhou 730070, Gansu, China;
    2. State Grid Jiangsu Economic Research Institute, Nanjing 210008, Jiangsu, China
  • Received:2016-10-26 Online:2017-08-20 Published:2016-10-26

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摘要： 针对风电机组的健康监测和预警评估,将基于环境荷载激励的模态参数识别和计算阶次分析方法应用于风电机组齿轮箱系统的在线模态分析。设计并构建了风电机组在线模态参数识别与故障诊断系统,通过试验模态与在线模态识别参数以及不同环境荷载激励条件下的在线模态识别参数的测试结果对比,证明在线模态参数识别方法的可行性和实时性,系统运行稳定,数据可靠,为风电机组在线模态实测,多种环境荷载激励作用下动态特性以及故障诊断研究积累了大量数据。

关键词: 计算阶次分析, 故障诊断, 在线模态参数识别, 风电机组

Abstract: According to the health monitoring and early warning evaluation of wind turbines, the modal parameter identification based on the ambient load excitation and the computed order analysis methods were applied in the online modal analysis of wind turbine gearbox system. An online modal parameter identification and fault diagnosis system for wind turbines was designed and developed. Comparison of test results between experimental modal and online modal parameter identification, and online modal identification parameters due to the different ambient load excitation condition, showed that methods for online modal parameter identification were feasible, real-time, stable and reliable. By now, a large amount of data for online modal measurement, dynamic characteristics due to varied ambient load excitation and fault diagnosis of wind turbines has been provided.

Key words: online modal parameter identification, wind turbines, computed order analysis, fault diagnosis

中图分类号: 

  • TM315
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