Research on railway vehicle modal parameter identification method based on drop impact load

Xiaolong He, Zhengyong Duan, Yangjun Wu, Dayong Tang, Shuai Peng, Bangbei Tang
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Abstract

This paper investigates the modal parameter identification technique utilizing a drop impact load. A 12-DOF mathematical model of a Railway Vehicle System (RWVS) was constructed, followed by theoretical calculations, simulation analysis, and tests with four different drop impact loads. The responses to these loads were inspected through FFT, and the modal frequencies of the RWVS were determined by the Peak Picking (P-P) method. The simulation demonstrated that four types of drop impact loads can activate the bounce, pitch, and roll modes of the RWVS. The theoretical calculation and simulation analysis revealed that the maximum error of modal frequency identification is no greater than 6.5%. The experimental results verified that the drop impact excitation method can be used to identify the modal parameters of a complex railway vehicle system, which is highly beneficial for the design and verification of the vehicle structure.
基于跌落冲击载荷的铁路车辆模态参数识别方法研究
本文研究了利用落锤冲击载荷的模态参数识别技术。首先构建了铁路车辆系统(RWVS)的 12-DOF 数学模型,然后进行了理论计算、仿真分析和四种不同落锤冲击载荷的测试。通过 FFT 检查了这些载荷的响应,并通过峰值采样 (P-P) 方法确定了 RWVS 的模态频率。模拟结果表明,四种下落冲击载荷可激活 RWVS 的弹跳、俯仰和滚动模态。理论计算和仿真分析表明,模态频率识别的最大误差不大于 6.5%。实验结果验证了落锤冲击激励方法可用于识别复杂铁路车辆系统的模态参数,对车辆结构的设计和验证大有裨益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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