摘要
介绍了经验模态分解法(EMD)和全息谱分析技术。运用EMD方法将机械设备振动信号分解,选择与原信号密切相关的信号重组,较好的消除了信号噪声,并对重组信号进行全息谱分析,使幅度、频率、相位有机结合,充分反映了设备振动形态特征。运用二维全息谱分析,可以得到转子振动在各阶倍频下的旋转方向、大小、形状以及各阶倍频之间的相互关系等信息。传统的信号处理方法都不能很好的消除信号噪声。此方法在转子振动信号故障诊断的应用,很好的消除了噪声,较好地反映了设备振动形态特征。
This article describes the empirical mode decomposition（EMD） and holospectrum analysis.To decompose the vibration signal of the equipment by EMD and re-organize the signal which closely associated with the original signal,aim to eliminate the noise signal better;and to analyze the holographic re-signal spectrum makes the amplitude,frequency and phase combine completely,reflecting the equipment vibration morphology fully.Particularly applying two-dimensional holospectrum can obtain the direction of rotation order harmonic,size,shape,and the relationship between order harmonic generation rotor vibrations.The traditional signal processing methods can not eliminate noise well.Applying this method to rotor vibration fault diagnosis eliminates noise and reflects the equipment vibration characteristics well,which has certain significance.
出处
《机械科学与技术》
CSCD
北大核心
2011年第11期1922-1926,共5页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(50975020)资助
关键词
经验模态分解
全息谱
故障诊断
empirical mode decomposition
holospectrum
fault diagnosis
