【摘要】：針對(duì)電機(jī)軸承早期故障特征十分微弱,容易被機(jī)器運(yùn)轉(zhuǎn)時(shí)的背景噪聲淹沒(méi)而難以識(shí)別的問(wèn)題,在分析峭度特性的基礎(chǔ)上,確定了信號(hào)峭度值和噪信比的數(shù)學(xué)關(guān)系。設(shè)計(jì)了受控于信噪比的峭度濾波器,并將其應(yīng)用于包絡(luò)分析的濾波環(huán)節(jié),以提取軸承故障的高頻調(diào)制信息,可避開(kāi)選取帶通濾波器時(shí)人為因素的影響。實(shí)驗(yàn)結(jié)果表明,對(duì)于軸承早期故障特征比較微弱的情況,基于峭度濾波器的診斷方法是有效的,將濾波后的信號(hào)進(jìn)行包絡(luò)分析可凸顯故障特征。
[Abstract]:Aiming at the problem that the early fault characteristics of motor bearings are very weak and are easily submerged by the background noise when the machine is running it is difficult to identify. Based on the analysis of the kurtosis characteristics the mathematical relationship between the signal kurtosis and the noise-to-signal ratio is determined. The kurtosis filter controlled by signal-to-noise ratio is designed and applied to the filtering link of envelope analysis to extract the high frequency modulation information of bearing fault and avoid the influence of human factors when selecting bandpass filter. The experimental results show that the diagnosis method based on kurtosis filter is effective for the weak fault feature of bearing in the early stage, and the envelope analysis of the filtered signal can highlight the fault feature.
【作者單位】： 河北科技大學(xué)電氣工程學(xué)院;河北科技大學(xué)信息科學(xué)與工程學(xué)院;
【基金】：河北省自然科學(xué)基金(f2006000101) 河北省高等學(xué)校科學(xué)技術(shù)研究青年基金項(xiàng)目(QN2014205) 河北科技大學(xué)五大平臺(tái)開(kāi)放基金(TY34)
【分類號(hào)】：TM307

【參考文獻(xiàn)】

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