摘要
时域平均常用于提取旋转机械振动信号的故障特征，但当旋转机械出现早期故障时，背景噪声常会使该方法失效，当旋转机械存在多种故障时，亦不能有效的分辨。通过比较分析小波变换、Hilbert-Huang变换和多分辨分析的Hilbert-Huang变换，在分析时域平均的基础上，提出了多分辨分析的经验模态分解方法（Multi-resolution Empirical Mode Decomposition ，MEMD）与频域几何平均相结合的诊断新方法。工程实例的应用结果表明，所提出的方法能有效地实现齿轮早期故障诊断。
Abstract
Time domain averaging is a common method to extract the fault characteristics of vibration signal of rotating machineries. However, when rotating machineries occurring earlier faults, time averaging will not be applicable because of the influence of the strong background noise. It also can’t distinguish the different faults from rotating machineries effectively. Via the comparative analysis of wavelet transform、Hilbert-Huang transform and Multi-resolution Hilbert-Huang transform, based on the analysis of time synchronous averaging, a new method which combines the method of Multi-resolution Empirical Mode Decomposition (MEMD) and Frequency Domain Geometrical Average is proposed. The application results show that the proposed method can realize the earlier gear fault detection effectively.
关键词
早期故障诊断 /
多分辨分析 /
Hilbert-Huang变换 /
频域平均
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Key words
earlier fault diagnosis /
multi-resolution analysis /
Hilbert-Huang transform /
frequency domain average
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鞠萍华;秦树人;秦毅;丁志宇.
多分辨EMD方法与频域平均在齿轮早期故障诊断中的研究[J]. 振动与冲击, 2009, 28(5): 97-101
Ju Ping-hua;Qin Shu-ren;Qin yi;Ding zhi-yu.
Research on Gear Earlier Fault Diagnosis by Method of Multi-resolution Empirical Mode Decomposition and frequency domain averaging[J]. Journal of Vibration and Shock, 2009, 28(5): 97-101
中图分类号：
TN911.6
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