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Applied Research on Segmented-Hilbert-Huang Transform Algorithm in Fault Feature Extraction of Main Reducer

机译:用于主减速器故障特征提取中分段 - 希尔伯特 - 黄变换算法的应用研究

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摘要

For the multi-time scale characteristics of vibration signal, a composite multi-frequency dictionary combining the low-frequency Fourier dictionary and the high-frequency impulse time-frequency dictionary is constituted, to decompose multi-component vibration signal into the combination of several one-component signals. The use of empirical model decomposition (EDM) in high-frequency impulse Component signal including feature information is to realize segmented Hilbert-Huang transform of signal and to acquire the time-frequency representation of every one-component signal, which is the process of fault information extraction of vibration signal. The application of the method in main reducer fault diagnosis verifies the engineering practicability and validity of the new algorithm.
机译:对于振动信号的多时间刻度特性,构成了组合低频傅里叶字典和高频脉冲时间频法字典的复合多频词典,以将多分量振动信号分解为几个组合-component信号。在包括特征信息的高频脉冲组件信号中使用经验模型分解(EDM)是实现信号的分段,并获取每个单分量信号的时频表示,这是故障过程振动信号的信息提取。该方法在主减速器故障诊断中的应用验证了新算法的工程实用性和有效性。

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