摘要
理论分析和实例证明,峭度指标等滚动轴承振动时域统计参量可以判定轴承工作是否正常,但不能给出更多信息。通过小波包分析对振动信号进行分解,并有针对性地对包含有故障特征频率的频段信号进行重构,能有效地滤去各种干扰信号,显示故障特征信息,为滚动轴承的故障诊断提供了一种快速有效的途径。
Theoretical analysis and examination were made and it is indicated that the present statistical parameters of time domain of rolling bearing vibration, such as the kurtosis index, can only provide the type information about a rolling bearing in normal or not. The feature spectrum of fault rolling bearing can be obtained by decomposing the vibration signal through wavelet packet analysis and then reconstructing the signal which ineluding fault feature spectrum, Thus, the information effectively helps the fault diagnosis of rolling bearing.
出处
《组合机床与自动化加工技术》
2008年第7期62-65,68,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
浙江省教育厅2006年度科研资助项目(20060359)
关键词
峭度指标
小波包分析
故障诊断
滚动轴承
kurtosis index
wavelet packet analysis
fault diagnosis
rolling bearing
