摘要
为了提取设备的故障特征,提出了基于时频切片分析的故障特征提取方法。首先采用基于频率切片小波变换分解振动信号,得到信号在全频带的时频分布。在此基础上根据其时频能量分布,选择时间频率切片区间进行细化分析,通过时频分割和信号重构得到选定区间的时频特征,实现了故障特征的分离。这种方法能够有效地获取正确的故障特征信息,在某炼油厂齿轮箱摩擦故障诊断中取得了较好的效果。
In order to extract fault features from vibration signal,a noval fault diagnosis approach using time-frequency slice analysis was proposed.Vibration signal was decomposed by applying frequency slice wavelet transform（FSWT）.Thereafter,on the basis of time-frequency energy distribution of the decomposed components,zoom analysis was adopted over those interested time-frequency slice intervals,selected for feature extraction.By making time-frequency segmentation and signal reconstruction,features in time and frequency domain were revealed over the selected slice intervals.As a result,the fault features were successfully separated from the vibration signal.The proposed approach can efficiently extract correct fault characteristic information for condition monitoring and fault diagnosis.A satisfactory effect has appeared on rub fault detection of a gear-box in an oil refinery.
出处
《振动与冲击》
EI
CSCD
北大核心
2011年第9期1-5,45,共6页
Journal of Vibration and Shock
基金
国家科技支撑计划项目(2008BAJ09B06)
关键词
频率切片小波变换
切片区间
细化分析
特征提取
故障诊断
frequency slice wavelet transform
slice interval
zoom analysis
feature extraction
fault diagnosis
