CAJ | 학술논문

为了更准确的诊断滚动轴承是否发生故障，提出了利用Teager能量算子求LMD分量能量信号，再做其1.5维谱的方法。局部均值分解（ Local Mean Decomposition，简称LMD）算法分解得到一组乘积函数分量，每一个分量都可近似看作一个线性平稳的单分量信号。 Teager能量算子可以追踪信号瞬态能量，使故障冲击成分突出。1.5维谱具有降低频谱中高斯噪声影响的作用。新的故障诊断方法结合了各方法的优点，能有效地提取滚动轴承故障信号的特征频率及其倍频。通过对实测滚动轴承外圈、滚动体、内圈故障信号的分析，有效地提取了各种故障的特征频率，验证了新方法在滚动轴承故障特征提取中的可靠性。
위료경준학적진단곤동축승시부발생고장，제출료이용Teager능량산자구LMD분량능량신호，재주기1.5유보적방법。국부균치분해（ Local Mean Decomposition，간칭LMD）산법분해득도일조승적함수분량，매일개분량도가근사간작일개선성평은적단분량신호。 Teager능량산자가이추종신호순태능량，사고장충격성분돌출。1.5유보구유강저빈보중고사조성영향적작용。신적고장진단방법결합료각방법적우점，능유효지제취곤동축승고장신호적특정빈솔급기배빈。통과대실측곤동축승외권、곤동체、내권고장신호적분석，유효지제취료각충고장적특정빈솔，험증료신방법재곤동축승고장특정제취중적가고성。
In order to diagnose the fault of roller bearing more accurately, this paper proposes a new method, which uses Teager operator to calculate the energy of local mean decomposition ( LMD) production functions and then figures out each 1.5 dimensional spectrum of them.LMD decomposes the fault signal into a group of product functions, each component can be considered as a linear stationary mono-component.Teager energy operator may calculate the transient energy of the fault signal, which can have a marked impact on roller bearing fault previously. 1.5 dimensional spectrum can reduce the effect of Gaussian noise in frequency spectrum.The new method com-bines the advantages of these algorithms, so it can extract fault characteristic frequency and its frequency doubling effectively.Through analyzing the test signals of outer raceway, ball and inner raceway fault, the paper achieved their fault characteristic frequency effectively and proved reliability of this method using in roller bearing fault fea-ture extraction.