CAJ | 학술논문

针对Morlet小波变换结果中的特征提取问题，对连续小波变换得到的小波系数矩阵进行奇异值分解（ SVD），分析了所获得的奇异值与Morlet小波变换结果中的特征信号以及噪声的对应关系。基于这种关系，通过选择合适的奇异值进行重构，清晰地提取到Morlet小波分解结果中的有效特征信息；进一步计算得到频率-能量谱，根据峰值位置能够提取冲击特征。将该方法应用于轴承振动信号的故障特征提取，并与其他方法进行了比较。结果表明，文中方法所获得的故障波形非常清晰，在低信噪比时具有较好的故障特征提取效果。
침대Morlet소파변환결과중적특정제취문제，대련속소파변환득도적소파계수구진진행기이치분해（ SVD），분석료소획득적기이치여Morlet소파변환결과중적특정신호이급조성적대응관계。기우저충관계，통과선택합괄적기이치진행중구，청석지제취도Morlet소파분해결과중적유효특정신식；진일보계산득도빈솔-능량보，근거봉치위치능구제취충격특정。장해방법응용우축승진동신호적고장특정제취，병여기타방법진행료비교。결과표명，문중방법소획득적고장파형비상청석，재저신조비시구유교호적고장특정제취효과。
Aiming at the feature extraction of Morlet wavelet transform results , the wavelet coefficient matrix obtained by the continuous Morlet wavelet transform is decomposed by singular value decomposition ( SVD ) .The relationship among the singular value , the feature signal and the noise in the Morlet wavelet transform results is analyzed .Based on this relationship , the effective feature information of wavelet transform results can be clearly extracted by selecting appropriate singular values for SVD reconstruction .Further calculation is carried out to obtain the frequency-energy spectrum , and the shock feature can be extracted according to the peak position of this spec -trum.Finally, the proposed method is applied to the fault feature extraction of bearing vibration signals and is com-pared with other methods .The results show that the proposed method can extarct the distinct fault waveforms and achieve a very good effect on fault feature extraction at a low signal-to-noise ratio(SNR).