%0 Journal Article
%T 风电机组传动系统振动监测研究进展<br>Research Progress of Vibration Monitoring for Wind Turbine Transmission System
%A 汤宝平
%A 罗雷
%A 邓蕾
%A 韩延
%J 振动.测试与诊断
%D 2017
%R 10.16450/j.cnki.issn.1004-6801.2017.01
%X 振动监测是当前风电机组传动系统状态监测的主要手段。首先，分析了风电机组传动系统振动监测策略和各部件振动特征提取流程，重点介绍了边频带能量因子、阶次谱边频带能量比等振动特征趋势指标；然后，分析指出解决现役风电机组因传动系统故障导致巨大经济损失的关键是进行风电机组传动系统早期故障预示，重点介绍了泛化流形学习的风电机组传动系统早期故障预示方法；最后，从系统架构、数据采集配置及监测分析方法等方面分析了现有的风电机组传动系统振动监测系统的功能与特点，指出了基于多源信息融合的大数据预测分析与智能维护将是风电机组健康管理的重要发展趋势。<br>The vibration monitoring method is the main approach of condition monitoring for wind turbine transmission system. The vibration monitoring strategy and the process of each component′s vibration feature extraction of wind turbine transmission system are analyzed firstly, and the trend indicators of vibration feature such as side band power factor (SBPF) and side band energy ratio (SER) are introduced especially. Then, it is pointed out that the key to retrieve the huge economic losses caused by the fault of wind turbine transmission system is incipient fault prediction for wind turbine transmission system, and the generalization manifold learning-based incipient fault prediction method for wind turbine transmission system is introduced especially. Finally, the function and characters of the existing vibration monitoring system for wind turbine transmission system are analyzed including system architecture, data acquisition configuration and monitoring analysis methods. Furthermore, it is pointed out that big data-based predictive analytics and intelligent maintenance based on multi-source information fusion technique would be the important development trend of health management for wind turbine transmission system.
%K 风电机组传动系统
%K 振动监测
%K 特征提取
%K 早期故障预示
%K 大数据&lt
%K br&gt
%K wind turbine transmission system
%K vibration monitoring
%K feature extraction
%K incipient fault prognosis
%K big data
%U http://zdcs.nuaa.edu.cn/ch/reader/view_abstract.aspx?file_no=201703001&flag=1