复杂工况下大型风电传动链故障诊断方法研究综述  

Review of fault diagnosis methods for large wind power drivetrain under complex operating conditions

作　　者：张方红 付大斌 杨钦云 张凯 ZHANG Fanghong;FU Dabin;YANG Qinyun;ZHANG Kai(The National Center for Applied Mathematics in Chongqing,Chongqing Normal University,Chongqing 401331,China;Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology,Guangzhou 510006,China;CSSC Haizhuang Wind Power Co.,Ltd.,Chongqing 401122,China)

机构地区：[1]重庆师范大学重庆国家应用数学中心,重庆401331 [2]中山大学广东省消防科学与智能应急技术重点实验室,广州510006 [3]中船海装风电有限公司,重庆401122

出　　处：《机械传动》2025年第4期156-168,共13页Journal of Mechanical Transmission

基　　金：国家自然科学基金项目(U2141245);重庆师范大学基金项目(22XLB008)。

摘　　要：【意义】故障诊断技术是保证风电机组运行效率并降低运维成本的关键。风电传动链作为风电机组的重要组成部分,了解其基本动力学模型对故障诊断具有重大意义。【分析】通过文献综述,详细介绍了风电传动链关键部件——主轴承、齿轮箱、发电机轴承的故障诊断方法。随着工况更加复杂、运行条件更加恶劣,传统的故障诊断方法受到限制。因此,复杂工况下风电传动链的故障诊断变得更为重要。结合近5年复杂工况下风电传动链故障诊断的发展,详细概述了当前复杂工况下大型风电传动链的故障诊断方法,同时探讨了风电传动链故障诊断技术未来的主要研究发展方向。[Significance] Fault diagnosis technology is the key to ensure the operation efficiency of wind turbines and reduce the operation and maintenance cost.As an important part of wind turbine,it is of great significance to understand its basic dynamic model for fault diagnosis.[Analysis] Through literature review,detailed fault diagnosis methods for key components of wind power drivetrain,namely the main bearing,gearbox,and generator bearing,were introduced.With more complex working conditions and harsher operating conditions,traditional fault diagnosis methods are limited,so the fault diagnosis of the wind power drivetrain under complex working conditions becomes more important.Combined with the development of fault diagnosis of the wind power drivetrain under complex working conditions in the past five years,the current fault diagnosis methods of large-scale wind power drivetrain under complex working conditions were summarized in detail,and the main research and development directions of the wind power drivetrain fault diagnosis technology in the future were discussed.

关 键 词：故障诊断 风电机组 复杂工况 信号处理 

分 类 号：TH174[机械工程—机械制造及自动化]