基于自适应小波线性组合振动信号分析的齿轮箱故障检测

Hanxin Chen, M. Zuo
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引用次数: 4

摘要

本文提出了一种基于Hilbert变换和自适应小波变换(AWT)的低频调制振动信号中齿轮裂纹识别方法。利用希尔伯特变换表示调制后的振动信号的包络,以表示调制频率。利用希尔伯特变换,应用AWT对调制后的振动信号进行处理。该方法通过优化后的小波变换将振动信号与啮合频率及其谐波、耦合频率、载波频率及其边带进行匹配。采用基于模型的AWT方法从调制后的振动信号中提取包络特征。用仿真和实验振动信号对该方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault detection of gearbox with vibration signal analysis by a linear combination of adaptive wavelets
In this paper, we propose a novel method for identification of gear crack from the low-frequency modulated vibration signal, based on Hilbert transform and adaptive wavelet transform (AWT). Hilbert transform is used to present the envelope of the modulated vibration signal to show the modulating frequency. AWT is applied to process the modulated vibration signal by Hilbert transform. The proposed AWT can match the vibration signal with the meshing frequency and its harmonics, the coupling frequency, the carrier frequency, and their sidebands by an optimized wavelet. The model-based method by AWT is applied to extract the envelop features from the modulated vibration signal. Both simulated and experimental vibration signals are used to test the proposed method.
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