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Research on the virtual reality of vibration characteristics in vehicle cabin based on neural networks

机译:基于神经网络的车厢振动特性的虚拟现实研究

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摘要

Abstract A finite element model of commercial vehicles was firstly built in the paper to study the virtual reality of vibration characteristics, and the top 6-order modal was then computed and compared with the experimental results to verify the reliability of the computational model. Then, a neural network model of the cabin was built. Through road tests, the excitation signal at the cabin suspension point and the response signal of interior vibration noise were measured under the idle condition and constant speed condition. The measured excitation signal was applied to the prediction model for frequency response analysis, in order to compute the interior noise within the range 20–200?Hz. The obtained simulation result of the vibration noise was compared with the experimental result and analyzed. As indicated from the analysis, the influence of excitation spectrum and the model can be reflected by the simulation response spectrum, which is consistent with the experimental result. The higher precision can be also obtained when the model is applied to predict the interior noise.
机译:摘要首先建立了商用车辆的有限元模型,以研究振动特性的虚拟现实,然后计算前6阶模态,并与实验结果进行比较,以验证计算模型的可靠性。然后,建造了机舱的神经网络模型。通过道路测试,在空闲状态下测量机舱悬架点处的激励信号和室内振动噪声的响应信号。将测量的激励信号应用于频率响应分析的预测模型,以计算20-200℃的内部噪声。将获得的振动噪声的模拟结果与实验结果进行了比较并分析。如图所示,激发谱和模型的影响可以由模拟响应谱反射,这与实验结果一致。当应用模型以预测内部噪声时,也可以获得更高的精度。

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