基于小波神经网络的液压泵故障类型识别
기우소파신경망락적액압빙고장류형식별
Fault Type Identification of Hydraulic Pump Based on Wavelet-neural Network
  • 万方数据
    机床与液压 궤상여액압
    MACHINE TOOL & HYDRAULICS
    2014年 11期 177-180 ,共4页

    董秋武%汪宝生

    동추무%왕보생

    液压泵%BP神经网络%小波包%特征值 液壓泵%BP神經網絡%小波包%特徵值
    액압빙%BP신경망락%소파포%특정치
    Hydraulic pump%BP neural network%Wavelet packet%Feature value
    根据液压泵发生故障所表现出来的特征，采用小波包能量值提取的办法作为故障类型识别的特征量，采用BP神经网络对输入的特征量进行识别。实验结果表明：采用小波神经网络对液压泵故障类型的识别可以取得满意的效果。
    근거액압빙발생고장소표현출래적특정，채용소파포능량치제취적판법작위고장류형식별적특정량，채용BP신경망락대수입적특정량진행식별。실험결과표명：채용소파신경망락대액압빙고장류형적식별가이취득만의적효과。
    According to feature shown during hydraulic pump fault,the sampling method of energy of wavelet packet was used to identify feature value of fault type.Then,these input feature value were identified by using BP neural network.The experimental re-sults demonstrate that satisfactory result can be obtained by using wavelet-neural network to identify fault types of hydraulic pump.
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