风电机组传动系统故障诊断平台开发  

Fault Diagnosis Platform of Wind Turbines Drive Train

作　　者：司文建[1] 王武[2] 

机构地区：[1]许昌学院计算机科学与技术学院,河南许昌461000 [2]许昌学院电气信息工程学院,河南许昌461000

出　　处：《机械设计与制造》2013年第9期234-236,共3页Machinery Design & Manufacture

基　　金：河南省科技厅科技攻关计划资助项目(122102210416);河南省教育厅科学技术研究重点项目(12A470007)

摘　　要：风电机组传动系统结构复杂,其振动故障主要涉及到滚动轴承、轴和齿轮箱等关键部件,分析了各个结构部件的典型故障和失效形式,给出了故障机理及对应的振动信号特征。振动信号作为风电机组传动链故障特征信息的载体,能够有效反应风电机组传动链的相关故障,针对风电机组中存在大量的暂态和非稳态信号的特点,提出通过小波变换进行频率提取。设计了基于测量单元下位机+基于PC上位机架构的故障诊断系统,信号处理模块由各种基于小波算法的软件包实现,功能强大,系统的可裁减性好。The wind turbine drive train system is with complex structure, and the vibration fault involves three key components, the typical fault and failure forms of rolling bearings, and shafts and gears in wind turbine drive train are analyzed, also the failure mechanism and corresponding vibration signal characteristics are proposed. Vibration signal is a carrier of fault features of the wind turbine driving chain, can effectively reflect most of the fault information of the wind turbine drive train. Wavelet transform for feature extraction is proposed as the characteristics of wind turbines in the presence of a large number of transient and non-stationary signals. The lower machine based on the measurement unit and the PC based host computer diagnosis system is designed, the signal processing module consists of a variety of packages based on wavelet algorithm implementation, and the diagnosis system is powerful and easily cut.

关 键 词：风电机组 振动特征提取 小波分析 故障诊断 平台开发 

分 类 号：TH16[机械工程—机械制造及自动化]