摘要
为实现对风力发电机组轴承故障的诊断,提出一种基于小波变换和峭度的诊断方法。首先应用自适应阈值小波降噪方法对风电机组中的振动信号进行降噪处理,凸显信号中的冲击成分;在此基础上,比较降噪后信号的峭度值与设定阈值,诊断风电机组轴承有无故障;确认有故障后,通过峭度图找出信号冲击成分最明显的频段,对故障源进行定位。实例验证结果表明,该方法能有效提高风电机组振动信号的信噪比,实现风力发电机组轴承故障的判断和准确定位。
In order to make fault diagnosis on wind turbine generator bearing,this paper presents a kind of method based on wavelet transform and kurtosis which is firstly to use the self-adaptive threshold wavelet de-noising method to de-noise vibration signals in the wind turbine generator and highlight impact signals.Then by comparing kurtosis after de-noising and setting threshold,it is able to determine whether there is a fault in the bearing.If there is a fault,the most prominent frequency band of the impact signal can be found out according to kurtosis diagram so as to locate the fault source.Example verification result indicates this method can effectively improve SNRs of vibration signals of the wind turbine generator and realize judgement and accurate location of bearing fault.
作者
曾军
陈艳峰
杨苹
邓小文
ZENG Jun;CHEN Yanfeng;YANG Ping;DENG Xiaowen(School of Electric Power,South China University of Technology,Guangzhou,Guangdong 510640,China;Guangdong Key Laboratory of Clean Energy,South China University of Technology,Guangzhou,Guangdong 510641,China;Guangdong Diankeyuan Energy Technology Co.,Ltd.,Guangzhou,Guangdong 510080,China)
出处
《广东电力》
2019年第1期46-51,共6页
Guangdong Electric Power
基金
国家科技支撑项目(2015BAA06B02)
广东省科技计划项目(2016B020245001)
关键词
小波变换
峭度
风力发电机组
故障诊断
故障特征参数
wavelet transform
kurtosis
wind turbine generator
fault diagnosis
fault characteristic parameter
