Fault Diagnosis for Rotor Systems Based on Wavelet Transform and EEMD
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摘要: 针对转子不平衡故障和滚动轴承微弱损伤性故障的复合故障诊断问题,提出了基于小波变换和总体平均经验模态分解(ensemble empirical mode decomposition,EEMD)的故障诊断方法,进行了复合故障的耦合特征分离和故障特征频率的提取。该方法首先应用小波对原始信号进行分解与重构;然后针对分解与重构出的低频信号进行频谱分析提取低频非调制故障特征;最后针对高频共振调制信号进行基于EEMD的解调分析,以准确提取调制故障特征。通过工程实例信号的分析结果表明,该方法能够提取轴承的损伤性故障特征。
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关键词:
- 复合故障 /
- 小波 /
- 总体平均经验模态分解 /
- 耦合特征
Abstract: Aiming at the composite fault diagnosis of the rotor failure and weak roller bearing fault， a fault diagnosis method was proposed based on the wavelet transform and the ensemble empirical mode decomposition by separating the coupling features of the composite fault and extracting the frequency of fault signals.Firstly original signals were decomposed and reconstructed by using the wavelet.Then non-modulation low-frequency fault feature was extracted using FFT for the low-frequency signals obtained from the decomposition and reconstruction of original signals.The high-frequency modulated signals from the decomposition and reconstruction of original were analyzed by envelop demodulation based on the ensemble empirical mode decomposition (EEMD)，and the modulated fault feature was extracted.Analyzing results of engineering signals indicated that the method can extract the composite fault feature of rolling bearings successfully.-
Key words:
- composite fault /
- wavelet /
- ensemble empirical mode decomposition /
- coupling feature
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