基于去相位算法和无数次滤波的轴承故障诊断

Liangliang Wang, Ping Gu, Xinghui Zhang, Kuo Chi
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引用次数: 0

摘要

轴承作为设备的关键部件,在电力传输中起着重要的作用。同时,它也容易失败。此外,它的失败可能会造成巨大的经济损失和灾难性的灾难。因此,我们需要研究意外轴承故障的解决方案。本文提出了一种组合诊断定轴齿轮箱轴承故障的方法。首先对故障信号进行减相处理,抑制齿轮啮合频率及其谐波;然后,将该后处理信号输入到无数次滤波中,增强轴承故障产生的脉冲信号。最后,我们进行了齿轮箱植入轴承故障试验,以验证所提出方法的有效性。结果表明,所提方法达到了预期的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bearing Fault Diagnosis Based on De-Phase Algorithm and Myriad Filtering
As a kind of key components of equipments, bearing plays an important role in power transmission. Meanwhile, it is prone to failure. Furthermore, its failure might cause great economic losses and catastrophic disasters. Therefore, we need to investigate the resolutions for unexpected bearing failure. In this paper, a combinational method is proposed to diagnose the bearing fault of fixed-axis gearbox. Fault signal was first processed by the de-phase algorithm to suppress the gear mesh frequency and its harmonics. Then, this post-processed signal was inputted to myriad filtering to enhance the impulsive signal produced by bearing faults. Finally, we conducted a gearbox implanted bearing fault test to validate the effectiveness of proposed methods. The results meet the expected effect of that proposed methods.
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