Composite fault diagnosis method based on empirical mode decomposition
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摘要: 針對轉子不平衡故障和滾動軸承微弱損傷性故障的復合故障診斷問題,提出了一種基于經驗模式分解的故障診斷方法,進行復合故障的耦合特征分離和軸承損傷性故障信號特征提取研究.該方法首先通過經驗模式分解將復合信號分解為若干個本征模函數(intrinsic mode function,IMF);然后通過計算各IMF與原始復合信號的相關系數確定包含故障特征信息的主要成分,除去虛假分量;最后針對主要成分中的低頻成分進行頻譜分析提出轉子故障特征,針對主要成分中的高頻成分進行Hilbert包絡解調提取調制故障特征,即軸承損傷性故障特征.仿真及實驗結果表明該方法的有效性和實用性.Abstract: Aimed at a composite fault of rotor failure and weak roller bearing fault, a fault diagnosis method based on empirical mode decomposition (EMD) was proposed to separate the coupling features of the composite fault and to extract the fault feature of the roller bearing. Signals were decomposed to obtain several intrinsic mode functions (IMF) by EMD. Main components are confirmed by calculating the correlation coefficient of every IMF and original composite signal, and false components were removed at the same time. Finally low-frequency rotor fault feature was extracted by FFT from the low-frequency component of main components, and high-frequency modulate feature of the roller bearing was extracted by Hilbert envelope demodulation from the high-frequency component of main components. Simulation and experiment analysis results indicate the validity and the practicability of the method proposed.
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