CAJ | 학술논문

针对数学形态学滤除白噪声能力不足的问题，提出了奇异值分解（ SVD）、局域均值分解（ LMD）和数学形态学相结合的特征提取方法。将信号进行奇异值分解，对分解后的主要成分取均值，然后进行局域均值分解，选取主要分量求和重构，再用形态学差值滤波器提取故障信号的频率特征。通过数值仿真试验和齿轮局部故障模拟实验，结果表明：该方法能够清晰地提取出故障信号的频率特征，并与奇异值分解形态滤波法相比较，证明了该方法的有效性。
침대수학형태학려제백조성능력불족적문제，제출료기이치분해（ SVD）、국역균치분해（ LMD）화수학형태학상결합적특정제취방법。장신호진행기이치분해，대분해후적주요성분취균치，연후진행국역균치분해，선취주요분량구화중구，재용형태학차치려파기제취고장신호적빈솔특정。통과수치방진시험화치륜국부고장모의실험，결과표명：해방법능구청석지제취출고장신호적빈솔특정，병여기이치분해형태려파법상비교，증명료해방법적유효성。
Aimed at the problem of shortage of capacity of the mathematical morphology filtering white noise, the feature extrac?tion method was proposed in combining of singular value decomposition ( SVD) , local mean decomposition ( LMD) and mathematical morphology. The SVD was used on the signal, the main ingredients in average were obtained after decomposition, and then the LMD was used. Main component was selected for sum re?fabricating, and then morphology difference filter was used to extract the frequency characteristics of the fault signal. Through numerical simulation test and local gear fault simulation experiment, the results show that this method can clearly extract the fault signal, and is compared with SVD and morphological filtering method, which has proved the ef?fectiveness of the proposed method.