CAJ | 학술논문

针对如何分离淹没在与转子转速相关的背景信号及其它噪声中的滚动轴承故障特征信号问题，提出将相空间重构与平稳子空间分析相结合的滚动轴承故障诊断方法。用相空间重构实现对滚动轴承故障振动信号升维；用平稳子空间对高维信号中平稳、非平稳源信号进行区分，并对峭度值最大的非平稳源信号进行最小熵解卷积降噪；对降噪信号进行包络谱分析提取轴承故障特征频率。仿真信号、故障诊断实例表明，诊断效果优于基于EMD的包络解调方法。
침대여하분리엄몰재여전자전속상관적배경신호급기타조성중적곤동축승고장특정신호문제，제출장상공간중구여평은자공간분석상결합적곤동축승고장진단방법。용상공간중구실현대곤동축승고장진동신호승유；용평은자공간대고유신호중평은、비평은원신호진행구분，병대초도치최대적비평은원신호진행최소적해권적강조；대강조신호진행포락보분석제취축승고장특정빈솔。방진신호、고장진단실례표명，진단효과우우기우EMD적포락해조방법。
Rollingbearing'sfaultfeaturesignalsarenon-stationary,transientandoftensubmergedinbackground signals associated with the components of rotating speed and other noises.How to separate the fault feature signals from the rolling bearing's blind sources is an important issue.A method combining the phase space reconstruction technique with the stationary subspace analysis (SSA)was proposed.The fault vibration signal's dimension was increased by the phase space technique and the non-stationary source components in the high-dimensional signals were distinguished from the stationary components by using the SSA.Then,the selected non-stationary component with the maximum kurtosis value was de-noised by the minimum entropy deconvolution (MED ).Finally,the de-noised non-stationary component was analyzed by the envelope spectrum to extract the fault characteristic frequency.The simulation and experiment results indicate that the proposed method can extract the fault frequency better than the envelope demodulation method based on empirical mode decomposition (EMD).