EMD降噪的关联维数在齿轮故障诊断中的应用研究

Gear fault diagnosis based on correlation dimension pre-processed with EMD

运用分形理论中的关联维数计算方法,对齿轮正常、齿根裂纹和断齿三种不同工况的振动信号进行识别。为了降低噪声对关联维数计算结果的影响,提出EMD滤波方法对采集的信号进行预处理。通过对仿真信号和齿轮箱实测信号的诊断,证明了该方法的可行性和有效性。

Three different conditions of a gear, i.e., normal condition, a crack in root of a tooth and a broken tooth were diagnosed by calculating the correlation dimension in the fractal theory. In order to weaken effect of noise on precision of calculation, a new filtering approach based on EMD was put forward to pre-process signals sampled. Through experiments on a gear box, this method was proved to be feasible and valid.