中国电机工程学报
中國電機工程學報
중국전궤공정학보
ZHONGGUO DIANJI GONGCHENG XUEBAO
2014年
35期
6355-6361
,共7页
唐贵基%邓飞跃%张超%胡爱军
唐貴基%鄧飛躍%張超%鬍愛軍
당귀기%산비약%장초%호애군
滚动轴承%倒谱编辑(CEP)%信号预白化%奇异值分解(SVD)%故障诊断
滾動軸承%倒譜編輯(CEP)%信號預白化%奇異值分解(SVD)%故障診斷
곤동축승%도보편집(CEP)%신호예백화%기이치분해(SVD)%고장진단
rolling bearing%cepstrum editing procedure (CEP)%signal pre-whitening%singular value decomposition (SVD)%fault diagnosis
为了有效提取轴承的故障特征,避免轴承损伤引起的冲击成分受到离散频率分量和强背景噪声的干扰,该文提出了一种新的基于倒谱编辑(cepstrum editing procedure,cep)信号预白化和奇异值分解(singular value decomposition, SVD)的轴承故障特征提取方法。通过CEP预白化处理增强了轴承故障的冲击特性,去除复杂振动信号中的周期性频率成分,产生了只包含背景噪声和碰撞损伤引起的非平稳冲击成分的白化信号。构造预白化信号的Hankel矩阵,进行奇异值分解,通过差分谱理论选择表征故障冲击成分的奇异值进行矩阵重构恢复信号,去除强背景噪声的干扰,实现对故障特征的提取。试验结果表明,该方法较为理想地提取了轴承滚动体和内圈的故障特征,并且在提取效果和运算效率方面要优于基于小波-SVD差分谱故障特征提取方法。
為瞭有效提取軸承的故障特徵,避免軸承損傷引起的遲擊成分受到離散頻率分量和彊揹景譟聲的榦擾,該文提齣瞭一種新的基于倒譜編輯(cepstrum editing procedure,cep)信號預白化和奇異值分解(singular value decomposition, SVD)的軸承故障特徵提取方法。通過CEP預白化處理增彊瞭軸承故障的遲擊特性,去除複雜振動信號中的週期性頻率成分,產生瞭隻包含揹景譟聲和踫撞損傷引起的非平穩遲擊成分的白化信號。構造預白化信號的Hankel矩陣,進行奇異值分解,通過差分譜理論選擇錶徵故障遲擊成分的奇異值進行矩陣重構恢複信號,去除彊揹景譟聲的榦擾,實現對故障特徵的提取。試驗結果錶明,該方法較為理想地提取瞭軸承滾動體和內圈的故障特徵,併且在提取效果和運算效率方麵要優于基于小波-SVD差分譜故障特徵提取方法。
위료유효제취축승적고장특정,피면축승손상인기적충격성분수도리산빈솔분량화강배경조성적간우,해문제출료일충신적기우도보편집(cepstrum editing procedure,cep)신호예백화화기이치분해(singular value decomposition, SVD)적축승고장특정제취방법。통과CEP예백화처리증강료축승고장적충격특성,거제복잡진동신호중적주기성빈솔성분,산생료지포함배경조성화팽당손상인기적비평은충격성분적백화신호。구조예백화신호적Hankel구진,진행기이치분해,통과차분보이론선택표정고장충격성분적기이치진행구진중구회복신호,거제강배경조성적간우,실현대고장특정적제취。시험결과표명,해방법교위이상지제취료축승곤동체화내권적고장특정,병차재제취효과화운산효솔방면요우우기우소파-SVD차분보고장특정제취방법。
In order to extract fault feature of bearing efficiently, and eliminate discrete frequencies caused by shock and strong background noise, a new method that based on combination of pre-whitening technology using cepstrum editing procedure(CEP) and singular value decomposition (SVD) theory was presented. Signal pre-whitening could enhance the impulsiveness of the bearing fault, and isolate the periodic frequencies in complex vibration signal. The pre-whitening signal only contained non-stationary impact components and background noise. Then a Hankel matrix was constructed for pre-whitening signal, and a group of singular values were obtained by SVD processing, the suitable singular values which represented fault of bearing were selected by difference spectrum, the reconstruction signal did not have strong noise interference and could extract the fault feature. The result shows that this method can efficiently extract the fault feature of defective rolling bearing with ball and inner faults, and has better extraction effect and operation efficiency than wavelet-SVD method.