摘要
应用形态滤波和HHT提取滚动轴承振动信号故障特征。通过形态组合滤波对信号进行预处理,对预处理后的信号进行EMD分解,把信号分解为若干个IMF的和,之后计算IMF的希尔伯特能量谱,提取振动信号的故障特征频率。本算法能够较准确地提取出滚动轴承振动信号的故障特征频率,为滚动轴承振动检测与故障诊断研究提供参考。
Both morphological filtering and HHT were used to extract the fault feature of rolling bearings , in which , the morphological filtering preprocesses the signal before implementing EMD on it for the sum of some IMFs, and then it calculates IMFs ’ Hilbert energy spectrum to extract fault characteristic frequency of the roll-ing bearing ’ s vibration signal , this provides the reference for the rolling bearing ’ s vibration detection and fault diagnosis .
出处
《化工自动化及仪表》
CAS
2014年第5期529-532,562,共5页
Control and Instruments in Chemical Industry
基金
黑龙江省长江学者后备支持计划资助项目(2012CJHB005)
黑龙江省教育厅科学技术研究项目(12531063)
关键词
故障诊断
形态滤波
滚动轴承
希尔伯特能量谱
EMD
IMF
morphological filtering
EMD
IMF
rolling bearing
Hilbert energy spectrum
