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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。
Due to the particularity of obtaining mine fan vibration signals, effective vibration signals are inundated by a large number of interference signals, which brings great difficulties to fault diagnosis of mine fan based on vibration signals. Therefore, a method of EMD-FFT vibration signal analysis is proposed, which combines empirical mode decomposition technique with Fourier analysis. EMD is used to decompose mine shaft vibration signals, spectrum analysis is carried out on the IMFs separately by FFT, and the signals are reorganized according to the frequency to eliminate high-frequency interference and obtain real vibration signals. By comparing the original signal FFT analysis with EMD-FFT analysis, it is proved that EMD-FFT is superior to direct FFT in mine fan vibration signal analysis.