發(fā)布時間：2018-03-27 08:36

  本文選題：液壓機械無級變速器　切入點：故障識別　出處：《機械設(shè)計與制造》2017年10期

【摘要】：對液壓機械無級變速器機械故障的振動和噪聲信號進行了分析:采用雙譜分析法識別齒輪故障,希爾伯特信號包絡(luò)法識別滾動軸承故障,小波變換信號分離法識別傳動箱故障。對液壓機械無級變速器液壓故障的試驗數(shù)據(jù)進行了研究:采用BP神經(jīng)網(wǎng)絡(luò)法識別電液比例伺服機構(gòu)故障,頻段分布法識別變量泵故障,核方法識別濕式離合器故障。研究表明:六種不同的方法對變速器的故障都有獨特的識別作用,應(yīng)根據(jù)變速器零部件的特性選擇恰當?shù)淖R別模式,以提高故障識別水平。
[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.
【作者單位】： 江蘇大學(xué)汽車與交通工程學(xué)院;安徽工程大學(xué)機械與汽車工程學(xué)院;
【基金】：國家自然科學(xué)基金項目(51575001) 安徽省自然科學(xué)基金項目(1508085ME70) 安徽工程大學(xué)科研啟動基金(2015YQQ002,2015YQQ003)
【分類號】：TH132.46;TH137
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本文編號：1670795