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A New Intelligent Fault Recognition Method for Rotating Machinery

机译:一种新的旋转机械智能故障识别方法

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In this paper, a novel method to recognize rotor fault pattern was proposed based on rank-order morphological filter, harmonic window decomposition, sample entropy and grey incidence. At first, the line structure element was selected for rank-order morphological filter to denoise the original signal. Then, the six feature frequency bands which contain the typical fault information were extracted by harmonic window decomposition that needs not decomposition;;and sample entropy of each band was calculated. Finally, these sample entropies could serve as the feature vectors, the grey incidence of different rotor vibration signals was calculated to identify the fault pattern and condition. Practical results show that this method can be used in fault diagnosis of rotating machinery effectively.
机译:在本文中,提出了一种基于秩序级形态过滤器,谐波窗分解,样品熵和灰色入射的新方法识别转子故障模式。首先,选择线结构元件用于等级顺序形态滤波器以去噪原始信号。然后,通过谐波窗口分解提取包含典型故障信息的六个特征频带,其不需要分解;和计算每个频带的样本熵。最后,这些样品熵可以用作特征向量,计算不同转子振动信号的灰色发生率以识别故障模式和条件。实际结果表明,该方法可有效地用于旋转机械的故障诊断。

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