液压机械无级变速器故障识别研究

发布时间：2018-03-27 08:36

  本文选题：液压机械无级变速器　切入点：故障识别　出处：《机械设计与制造》2017年10期

【摘要】：对液压机械无级变速器机械故障的振动和噪声信号进行了分析:采用双谱分析法识别齿轮故障,希尔伯特信号包络法识别滚动轴承故障,小波变换信号分离法识别传动箱故障。对液压机械无级变速器液压故障的试验数据进行了研究:采用BP神经网络法识别电液比例伺服机构故障,频段分布法识别变量泵故障,核方法识别湿式离合器故障。研究表明:六种不同的方法对变速器的故障都有独特的识别作用,应根据变速器零部件的特性选择恰当的识别模式,以提高故障识别水平。
[Abstract]:The vibration and noise signals of mechanical faults of hydraulic machinery stepless transmission are analyzed. The gear faults are identified by bispectral analysis, and the rolling bearing faults are identified by Hilbert signal envelope method. Wavelet transform signal separation method is used to identify the fault of transmission box. The test data of hydraulic failure of hydraulic mechanical stepless transmission are studied. BP neural network method is used to identify the fault of electro-hydraulic proportional servo mechanism and frequency band distribution method to identify the fault of variable pump. The kernel method is used to identify the wet clutch fault. The research shows that the six different methods have a unique effect on the fault identification of the transmission, and the appropriate identification mode should be selected according to the characteristics of the parts and components of the transmission in order to improve the level of fault identification.
【作者单位】： 江苏大学汽车与交通工程学院;安徽工程大学机械与汽车工程学院;
【基金】：国家自然科学基金项目(51575001) 安徽省自然科学基金项目(1508085ME70) 安徽工程大学科研启动基金(2015YQQ002,2015YQQ003)
【分类号】：TH132.46;TH137
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本文编号：1670795