Hilbert-Huang变换的改进及其在轴承故障诊断中的应用

Modification of Hilbert-Huang transformation and its application to fault diagnosis of bearings

针对传统EMD算法中因极值点选择和迭代终止条件导致的模态混叠问题,提出二次迭代方法和基于IMF有限正交性的迭代终止条件,改进算法提高了算法精度,避免了模态混叠的出现。仿真结果表明,相对于传统算法,该改进算法可有效提高对混叠信号的拆分能力,并将此用于滚动轴承的故障诊断,结果证明了该方法的有效性和优越性。

In view of modal mixture and overlay due to selection of extreme point and iterative termination conditions in conventional EMD （Empirical Mode Decomposition） algorithm, secondary iterative sifting equation and iterative termination conditions based on IMF （Intrinsic Mode Function） finite orthogonality were proposed to improve the algorithm, thus the algorithm precision enhanced and the modal mixture and overlay was avoided. Simulation results showed that the improved algorithm could enhance the ability to separate the mixed and overlaid signals compared with conventional algorithms. In addition, it was applied to the fault diagnosis of the rolling bearings. The improve algorithm proved effective and superior through test results.