【摘要】：針對(duì)滾動(dòng)軸承滾珠磨損故障特征難以提取的問題,提出一種基于多脈沖激勵(lì)法下的Volterra級(jí)數(shù)核的求解算法.該方法是一種非線性系統(tǒng)模型的"交叉"診斷法,利用軸承系統(tǒng)輸入輸出的采樣信號(hào),建立Volterra非線性辨識(shí)系統(tǒng)模型,并運(yùn)用多脈沖激勵(lì)Volterra低階核求解算法,將得到的低階核通過時(shí)域和頻域進(jìn)行對(duì)比來判斷軸承當(dāng)前所處的運(yùn)行狀態(tài).該文以無心車床主軸軸承為例進(jìn)行實(shí)驗(yàn)驗(yàn)證,并與傳統(tǒng)的小波分析法對(duì)比得出:多脈沖激勵(lì)法能夠方便準(zhǔn)確地提取軸承的故障特征,該方法對(duì)此類故障的診斷具有一定的借鑒意義.
[Abstract]:In order to solve the problem that the ball wear fault feature of rolling bearing is difficult to extract, a solution algorithm of Volterra series kernel based on multi-pulse excitation method is proposed. This method is a "cross" diagnosis method for nonlinear system model. The Volterra nonlinear identification system model is established by using the input and output sampling signals of the bearing system, and the low order kernel solution algorithm of multi-pulse excitation Volterra is used. The low order kernels are compared in time domain and frequency domain to determine the current operating state of the bearing. This paper takes the spindle bearing of the centerless lathe as an example, and compares it with the traditional wavelet analysis method. It is concluded that the multi-pulse excitation method can extract the fault characteristics of the bearing conveniently and accurately. This method can be used for reference in the diagnosis of this kind of fault.
【作者單位】： 西安建筑科技大學(xué)機(jī)電工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金青年科學(xué)基金(51105292)~~
【分類號(hào)】：TH133.33

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