噪声与振动控制
譟聲與振動控製
조성여진동공제
NOISE AND VIBRATION CONTROL
2015年
1期
235-239
,共5页
振动与波%故障诊断%小波变换%集合经验模态分解%Teager能量谱分析
振動與波%故障診斷%小波變換%集閤經驗模態分解%Teager能量譜分析
진동여파%고장진단%소파변환%집합경험모태분해%Teager능량보분석
vibration and wave%fault diagnosis%wavelet transform%ensemble empirical mode decomposition (EEMD)%Teager energy spectrum analysis
机械故障的声发射信号中往往掺杂着各种干扰和噪声，为解决这一问题，提出了小波变换、集合经验模态分解（Ensemble Empirical Mode Decomposition，EEMD）和马氏距离相结合的滚动轴承故障诊断方法；首次将马氏距离引入到轴承声发射信号的故障诊断中。该方法首先对故障轴承的声发射信号进行小波去噪处理，再对去噪后的信号进行EEMD分解，将其分解为多个固有模式函数（简称IMF）。其次采用马氏距离的方法消除EEMD分解结果中的虚假分量，提取能够反映轴承故障特征的IMF分量，突出高频共振成分。最后，通过瞬时Teager能量的Fourier频谱识别轴承故障的特征频率。仿真信号和滚动轴承外圈声发射信号的实例分析表明：此方法能很好地去除混杂在轴承声发射信号中的噪声，准确地识别出轴承故障的部位。
機械故障的聲髮射信號中往往摻雜著各種榦擾和譟聲，為解決這一問題，提齣瞭小波變換、集閤經驗模態分解（Ensemble Empirical Mode Decomposition，EEMD）和馬氏距離相結閤的滾動軸承故障診斷方法；首次將馬氏距離引入到軸承聲髮射信號的故障診斷中。該方法首先對故障軸承的聲髮射信號進行小波去譟處理，再對去譟後的信號進行EEMD分解，將其分解為多箇固有模式函數（簡稱IMF）。其次採用馬氏距離的方法消除EEMD分解結果中的虛假分量，提取能夠反映軸承故障特徵的IMF分量，突齣高頻共振成分。最後，通過瞬時Teager能量的Fourier頻譜識彆軸承故障的特徵頻率。倣真信號和滾動軸承外圈聲髮射信號的實例分析錶明：此方法能很好地去除混雜在軸承聲髮射信號中的譟聲，準確地識彆齣軸承故障的部位。
궤계고장적성발사신호중왕왕참잡착각충간우화조성，위해결저일문제，제출료소파변환、집합경험모태분해（Ensemble Empirical Mode Decomposition，EEMD）화마씨거리상결합적곤동축승고장진단방법；수차장마씨거리인입도축승성발사신호적고장진단중。해방법수선대고장축승적성발사신호진행소파거조처리，재대거조후적신호진행EEMD분해，장기분해위다개고유모식함수（간칭IMF）。기차채용마씨거리적방법소제EEMD분해결과중적허가분량，제취능구반영축승고장특정적IMF분량，돌출고빈공진성분。최후，통과순시Teager능량적Fourier빈보식별축승고장적특정빈솔。방진신호화곤동축승외권성발사신호적실례분석표명：차방법능흔호지거제혼잡재축승성발사신호중적조성，준학지식별출축승고장적부위。
The acoustic emission signal of mechanical faults is usually mixed with various kinds of interference and noise. In this article, a method of fault diagnosis of roller bearings was proposed using wavelet transform and EEMD-mahala-nobis distance. First of all, the original acoustic emission signals were disposed by wavelet-denoising and decomposed into several stationary intrinsic mode functions (IMF) by EEMD. Then, the false IMFs of EEMD were eliminated by mahalano-bis distance method so that the IMF components which could reflect the characteristics of bearing faults could be extracted. Finally, the Fourier spectrum of the transient Teager energy was used to recognize the characteristic frequencies of the bear-ing faults. Comparison of simulation signal with the measurement emission signal of the bearing with outer race faults show that the method can effectively remove the noise in the fault mixed signals, and identify the location of the bearing fault accu-rately.
