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路面功率譜密度識別的仿真
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    摘要:

    路面激勵是汽車平順性和操縱穩(wěn)定性研究中的重要因素。提出了一種基于徑向基函數(shù)(RBF)神經(jīng)網(wǎng)絡(luò)識別路面功率譜密度的仿真研究方法,。建立了4自由度汽車振動模型,,利用Matlab軟件仿真得到汽車車身質(zhì)心垂直加速度功率譜密度和俯仰角加速度功率譜密度。應(yīng)用RBF神經(jīng)網(wǎng)絡(luò)建立了汽車車身質(zhì)心垂直加速度功率譜密度,、俯仰角加速度功率譜密度和路面功率譜密度之間的非線性映射模型,。仿真結(jié)果表明:該方法思路明確,抗噪聲能力比較強,,識別的精確度高,。

    Abstract:

    Road surface excitation is an important factor in the research of vehicle riding and maneuver stability. Based on radial basis function (RBF) neural networks, a simulation research method of road surface power spectrum density (PSD) identification was put forward. A four-degree-of-freedom vehicle vibration model was set up and the PSDs for vertical acceleration and pitching angular acceleration of vehicle body centroid were got through Matlab simulation. The nonlinear mapping relation among the PSD of vehicle body centroid vertical acceleration, pitching angular acceleration and the road surface were found by RBF neural networks. The simulation results show that the proposed method has the feature of a good anti-noise performance and high identification accuracy.

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張麗霞,趙又群,徐培民,吳杰.路面功率譜密度識別的仿真[J].農(nóng)業(yè)機械學(xué)報,2007,38(5):15-18.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(5):15-18.

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