采用D-S证据推理的电机转子故障诊断
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    摘要:

    提出了采用DS(DempsterShafer)证据理论对感应电机转子断条故障进行识别的故障诊断 方法。基于小波包变换的频率划分特性,对定子三相电流信号进行小波包分解,利用节点系数 的均方根值构建电机转子故障的特征矢量(证据体);利用明氏距离测度构造基本可信度分配 函数,求取证据体对转子故障所赋予的基本概率分配函数值,然后根据DS证据融合规则进行 融合处理,实现了对电机转子故障的准确识别。试验结果表明,该方法可实现转子断条故障的可靠诊断。

    Abstract:

    A method based on the DempsterShafer (DS) evidential theory was pr es ented and applied to diagnose broken rotor bars of induction motors. Wavelet pac kets decomposition of the threephase stator current was carried out according t o the frequency partition characteristics of the wavelet packets transformation. The fault characteristic vector (evidence) of the broken rotor bars was establi shed by the root mean square (RMS) value of the wavelet nodes coefficient; Minko waki distance measurement was used to construct basic reliability distribution f unction and to determine its value which was evidence as a result of the rotor f aults. By using the DS evidential fusion algorithm, the broken rotor bar fault s of the motor was accurately identified. The experimental results show that the proposed method can diagnose the broken rotor bars effectively.

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  • 收稿日期:2010-01-04
  • 最后修改日期:2010-03-29
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