基于参考模型的汽车变速箱诊断

I. Komorska
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引用次数: 3

摘要

提出了一种诊断汽车变速箱磨损的方法。该程序可在驾驶过程中自动实现。为了能够进行这种诊断,在同步平均信号的基础上,为一个新的变速箱(在良好的技术条件下)创建了振动信号的参考模型。为了实现机载程序,该模型必须易于识别。抛弃了复杂的结构模型,采用简单的抽象振动信号模型。提出了三种建模方法:谐波序列模型、参数自回归移动平均模型和小波模型。在确定的驱动时刻记录当前振动信号,然后与参考模型进行比较。每次大修或更换传动系统元件后,应重新确定参考模型。诊断是通过比较参考模型的测量值和当前测量的经过充分处理的信号来完成的。在菲亚特Punto 5速变速箱汽车上进行了主动试验,验证了该方法的有效性。所述方法可构成对车载驱动系统机械故障的补充。主齿轮、差动齿轮、铰接接头、轴承、发动机排气阀和发动机头垫圈的缺陷可扩大此程序。
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AUTOMOBILE GEARBOX DIAGNOSTICS ON THE BASIS OF THE REFERENCE MODEL
A method of diagnostics of the automobile gearbox wearing out is presented in this paper. The procedure can be automatically realised during driving. To be able to perform such diagnostics the reference model of the vibration signal on the basis of the synchronously averaged signal was created for a new gearbox (in a good technical con­dition). In order to realize the procedure on-board this model must be easily identifiable. A complicated structural model was given up for the simpler model of the abstract vibrations signal. Three ways of modelling were pre­sented: harmonic series, parametric ARMA (Auto Regressive Moving Average) model, and the wavelet model. The current vibration signal is recorded at the determined moment of driving and then compared with the referen­ce model. After each overhaul or exchange of drive system elements the reference model should be identified again. Diagnostics is being done by comparing measures for the reference model and the currently measured - adequately processed - signal. The method was verified in the active experiment performed on the Fiat Punto automobile with a 5-speed gearbox. The described method can constitute the supplementation of on-board auto­mobile system by the mechanical failures of the drive system. This procedure can be broadened by defects of the main gear, differential gear, articulated joints, bearing, engine exhaust valves, and engine head gasket.
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来源期刊
International Journal of Mechanics and Control
International Journal of Mechanics and Control Engineering-Computational Mechanics
CiteScore
2.10
自引率
0.00%
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0
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