本文選題：回轉(zhuǎn)支承 + 圓域分析��； 參考：《振動(dòng)與沖擊》2017年09期

【摘要】：為解決真實(shí)工況下大型回轉(zhuǎn)支承振動(dòng)信號(hào)背景噪聲大、常用故障診斷方法難以適用的問(wèn)題,提出了一種基于圓域分析的振動(dòng)信號(hào)處理方法。將時(shí)域信號(hào)進(jìn)行圓域轉(zhuǎn)換,并按一定角度將轉(zhuǎn)換后的圓域信號(hào)劃分成多個(gè)區(qū)域;判斷各區(qū)域信號(hào)鄰域相關(guān)離散點(diǎn)擬合橢圓的傾角方向,得到回轉(zhuǎn)支承整圈對(duì)應(yīng)的多個(gè)異常向量;以異常向量的平均向量作為圓域分析的特征向量,分析其均值、方差、歪度和峭度指標(biāo)的變化情況,實(shí)現(xiàn)回轉(zhuǎn)支承的故障診斷。對(duì)某型號(hào)回轉(zhuǎn)支承進(jìn)行了加速壽命試驗(yàn),結(jié)果表明,該方法能夠有效診斷出回轉(zhuǎn)支承滾道的區(qū)域滑移、點(diǎn)蝕等初期故障,相比常見(jiàn)的時(shí)域特征、小波分析等方法準(zhǔn)確度更高,故障可識(shí)別度更強(qiáng),因此可以用于實(shí)際工況下回轉(zhuǎn)支承的故障診斷。
[Abstract]:In order to solve the problem that the background noise of vibration signal of large slewing bearing is large and the common fault diagnosis method is difficult to apply in real working condition, a vibration signal processing method based on circle analysis is proposed. The time domain signal is converted in circle domain, and the transformed circle signal is divided into several regions according to certain angle, and the relative discrete points of each region signal neighborhood fit the obliquity direction of the ellipse, and many abnormal vectors corresponding to the whole circle of the slewing support are obtained. The mean vector of abnormal vector is used as the eigenvector of circle domain analysis, and the variation of mean value, variance, skew degree and kurtosis index is analyzed, and the fault diagnosis of slewing bearing is realized. The accelerated life test of a certain type of slewing bearing shows that the method can effectively diagnose the initial faults such as slip and pitting of the raceway of the slewing bearing, and the wavelet analysis method is more accurate than the common time domain features. It can be used in the fault diagnosis of slewing bearing under actual working condition.
【作者單位】： 南京工業(yè)大學(xué)機(jī)械與動(dòng)力工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51375222;51175242)
【分類號(hào)】：TH17

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