CAJ | 학술논문

针对轴承故障成分常以周期性冲击成分出现在振动信号中，而冲击响应成分常被强大噪声淹没，造成轴承故障特征提取困难等问题，将集成经验模态分解（EEMD）与改进形态滤波方法相结合，在本征模态函数（IMF）及形态学结构元素（SE）选取时均以峭度准则为依据，对筛选出的 IMF 分量进行信号重构后，再进行基于峭度准则的改进形态滤波方法处理。结果表明，该方法可避免共振解调中中心频率及滤波频带选取，自适应性较好；通过对实际滚动轴承内外圈故障分析，该方法可清晰准确提取到故障特征信息，噪声抑制效果好，可用于轴承故障精确诊断。
침대축승고장성분상이주기성충격성분출현재진동신호중，이충격향응성분상피강대조성엄몰，조성축승고장특정제취곤난등문제，장집성경험모태분해（EEMD）여개진형태려파방법상결합，재본정모태함수（IMF）급형태학결구원소（SE）선취시균이초도준칙위의거，대사선출적 IMF 분량진행신호중구후，재진행기우초도준칙적개진형태려파방법처리。결과표명，해방법가피면공진해조중중심빈솔급려파빈대선취，자괄응성교호；통과대실제곤동축승내외권고장분석，해방법가청석준학제취도고장특정신식，조성억제효과호，가용우축승고장정학진단。
Bearing faults are always observed as cyclical impulses in the vibration signal.In order to effectively remove the strong noise immersing the impulsive response signals and detect the cyclic impulses in the signals for bearing faults diagnoisis,a hybrid method combining the ensemble empirical mode decomposition (EEMD)method with an improved morphological filtering based on kurtosis criterion was proposed.In the method,a new decision strategy of intrinsic mode function (IMF)and morphological structure element (SE)was suggested in accordance with the kurtosis criterion.The signal reconstructed by the selected IMFs was processed by the improved morphological filtering based on kurtosis criterion.The method presented avoids the selection of center frequency and filter band in resonance demodulation method and has good adaptability.When analyzing the inner and outer ring faults of rolling bearing,the method shows its good ability of distinctly and accurately extracting the fault information and the noise is well suppressed.