摘要
由于获取矿井风机振动信号的特殊性,致使有效的振动信号被大量干扰信号所淹没,给基于振动信号的矿井风机故障诊断带来很大困难。为此,提出一种EMD-FFT振动信号分析方法,该方法将经验模态分解技术与傅里叶分析相结合。采用EMD对矿井风机振动信号进行分解,用FFT对分量(IMF)分别进行频谱分析,并将其按频率重组,剔除高频干扰,获取真实振动信号。通过将原始信号FFT直接分析与EMD-FFT分析对比研究,证明EMD-FFT较直接FFT在矿井风机振动信号分析中的优越性。
The effective vibration signals are drowned by a large number of interfering signal, because of the specificity of mine fan vibration signal. It is difficult for vibration signal for mine fan fault diagnosis which based on vibration signal. For this, the paper proposes a EMD-FFT vibration signal analysis method, which combined empirical mode decomposition technique with Fourier analysis. The mine fan vibration signal decomposed by EMD decomposition, analyzed the spectrum of component （IMF） by FFT respectively. According to the frequency, recombine the signal, eliminate the high frequency interference, and obtain the real vibration signal. The result of contrast between FFT and EMD-FFT proved that the EMD-FFT is more of superiority than FFT directly in analyzing vibration signal analysis of the mine fan.
出处
《煤矿机械》
北大核心
2014年第9期282-285,共4页
Coal Mine Machinery
关键词
振动信号
经验模态分解
固有模态函数
信号分析
vibration signal
empirical mode decomposition
intrinsic mode function
signal analysis
