摘要
针对滚动轴承故障诊断问题,在分析了基于二进制小波包分解的增强峭度图方法的不足后,提出了基于谐波小波包分解的改进增强峭度图方法。通过计算故障信号的改进增强峭度图,筛选出峭度值最大的最优节点,利用最优节点处的谐波小波包系数进行信号重构,并对重构信号做增强包络谱分析,利用故障特征频率的理论计算值与增强包络谱中峰值明显的谱线进行对比,从而对轴承故障类型做出判断。运用所提出的诊断方法分别对滚动轴承内圈故障模拟、实测信号进行分析,结果表明,该方法具有一定的可靠性,能够满足实际的工程需要。
To effectively extract the fault features of rolling bearings,an improved enhanced kurtogram method based on harmonic wavelet packet decomposition was presented after analyzing the shortcoming of conventional enhanced kurtogram method based on binary wavelet packet decomposition.The node with the maximum kurtosis value was selected after the improved enhanced kurtogram of fault signal was computed,then the harmonic wavelet packet coefficient of the optimal node was used to reconstruct the signal and the reconstructed signal was successively analysed by using the enhanced envelope spectrum.The fault type of rolling bearing was judged by comparing the theoretical calculation value of fault characteristic frequency with the spectral lines whose amplitudes were obvious in the enhanced envelope spectrum. The simulated inner fault signal and the measured inner fault signal of rolling bearings were analyzed by the proposed method,and the diagnosis results show that the new method is reliable and can meet the actual requirements.
出处
《振动与冲击》
EI
CSCD
北大核心
2014年第13期53-58,共6页
Journal of Vibration and Shock
关键词
改进增强峭度图
增强包络谱
滚动轴承
故障诊断
improved enhanced kurtogram
enhanced envelope spectrum
rolling bearings
fault diagnosis
