【摘要】：針對(duì)滾動(dòng)軸承故障信號(hào)非線性、非平穩(wěn)特征導(dǎo)致的故障頻率難以提取的問題,提出一種基于補(bǔ)充總體平均經(jīng)驗(yàn)?zāi)B(tài)分解(Complementary EEMD,CEEMD)和奇異值差分譜結(jié)合的滾動(dòng)軸承故障診斷方法。CEEMD分解向原信號(hào)成對(duì)地添加符號(hào)相反的白噪聲,幾乎消除殘留白噪聲的影響。首先,對(duì)故障信號(hào)利用CEEMD算法進(jìn)行分解,得到若干IMF(Intrinsic Mode Function)分量,然后運(yùn)用相關(guān)系數(shù)—峭度準(zhǔn)則對(duì)IMF分量進(jìn)行篩選并重構(gòu),再對(duì)重構(gòu)信號(hào)進(jìn)行奇異值分解,并求出奇異值差分譜,根據(jù)奇異值差分譜理論進(jìn)行消噪和重構(gòu),最后對(duì)重構(gòu)信號(hào)進(jìn)行Hilbert包絡(luò)譜分析,提取故障頻率。實(shí)驗(yàn)結(jié)果表明,提出的方法,能精確地提取滾動(dòng)軸承的故障頻率。
[Abstract]:Aiming at the problem that the fault signal of rolling bearing is nonlinear and the fault frequency caused by non-stationary characteristic is difficult to extract, A rolling bearing fault diagnosis method based on complementary average empirical mode decomposition (Complementary EEMD,CEEMD) and singular value differential spectrum is proposed. The white noise with opposite symbols is added to the original signal in pairs, which almost eliminates the influence of residual white noise. Firstly, the fault signal is decomposed by CEEMD algorithm, and some IMF (Intrinsic Mode Function) components are obtained. Then the correlation coefficient kurtosis criterion is used to screen and reconstruct the IMF component, and then the singular value decomposition of the reconstructed signal is carried out, and the singular value difference spectrum is obtained. According to the singular value difference spectrum theory, the noise reduction and reconstruction are carried out. Finally, the Hilbert envelope spectrum of the reconstructed signal is analyzed, and the fault frequency is extracted. The experimental results show that the proposed method can accurately extract the fault frequency of rolling bearings.
【作者單位】： 華北電力大學(xué)能源動(dòng)力與機(jī)械工程學(xué)院;
【分類號(hào)】：TH133.33

【相似文獻(xiàn)】

相關(guān)期刊論文 前7條

1 王志武;孫虎兒;劉維雄;;基于局部均值分解和奇異值差分譜的滾動(dòng)軸承故障診斷研究[J];機(jī)械科學(xué)與技術(shù);2014年09期

2 于德介;陳淼峰;程軍圣;楊宇;;基于EMD的奇異值熵在轉(zhuǎn)子系統(tǒng)故障診斷中的應(yīng)用[J];振動(dòng)與沖擊;2006年02期

3 姚春江;毋文峰;陳小虎;蘇勛家;;基于源信號(hào)包絡(luò)矩陣奇異值的機(jī)械故障診斷方法[J];機(jī)床與液壓;2014年13期

4 張營(yíng);左洪福;佟佩聲;陳志雄;白芳;;基于譜插值和奇異值差分譜的滾動(dòng)軸承靜電監(jiān)測(cè)信號(hào)去噪方法[J];航空動(dòng)力學(xué)報(bào);2014年08期

5 陶新民;杜寶祥;徐勇;;基于HOS奇異值譜的SVDD軸承故障檢測(cè)方法[J];振動(dòng)工程學(xué)報(bào);2008年02期

6 侯者非;楊杰;張雪;;基于復(fù)小波和奇異值比譜的軸承故障檢測(cè)方法[J];武漢理工大學(xué)學(xué)報(bào);2011年01期

7 ;[J];;年期

，

本文編號(hào)：2217971