作者：蒋宇涵, 华春蓉, 熊丽波, 王瑞, 董大伟

作者单位：西南交通大学机械工程学院，四川 成都 610031

关键词：列车轮对;裂纹识别;变分模态分解;Kriging代理模型;轨道不平顺

摘要：

为实现实际运行工况中的轮对裂纹特征提取及裂纹参数识别，利用Abaqus建立含裂纹轮对系统的有限元模型，仿真轨道随机不平顺激励下的轮对振动响应，并采用变分模态分解（VMD）和快速傅里叶变换（FFT）提取不同运行速度下的轮对裂纹特征参数。其次，利用Kriging代理模型构建裂纹参数和IMF分量中1X、2X谐波成分幅值的关系。最后将裂纹参数的识别问题转换为目标函数的优化问题，使用Kriging代理模型代替有限元计算，利用遗传算法搜索目标函数的最优解，从而实现轮对裂纹参数的定量识别。通过对轨道随机不平顺激励下的多组不同轮对裂纹参数的识别，裂纹位置识别准确率达到100%，深度识别准确率达到92.12%，可为实际工况中的轮对裂纹参数识别提供借鉴。

Vibration characteristics analysis and crack parameters identification of cracked wheelset
JIANG Yuhan, HUA Chunrong, XIONG Libo, WANG Rui, DONG Dawei
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Abstract: In order to extract the feature of wheelset cracks and identify the crack parameters in actual operating conditions, the finite element model of the cracked wheelset system is established by Abaqus to simulate the vibration response of wheelset under random track irregularity excitation. And then the characteristic parameters of wheelset crack at different speed are extracted by using variational mode decomposition (VMD) and fast Fourier transform (FFT). Secondly, the relationship between the crack parameters and the amplitude of the 1X, 2X harmonic components in the IMF component is constructed using Kriging surrogate model. Finally, the problem of identifying crack parameters is transformed into an optimization problem of objective function. Substituting Kriging surrogate model for finite element calculation, genetic algorithm is used to search for the optimal solution of the objective function, so as to achieve the quantitative identification of the wheelset crack parameters. By identifying different parameters of the cracks in the wheelset under the excitation of random track irregularity, the position identification accuracy reaches 100%, and the depth identification accuracy reaches 92.12%, which can provide a reference for the wheelset crack parameters identification in actual working conditions.
Keywords: train wheelset;crack identification;VMD;Kriging surrogate model;track irregularity
2022, 48(1):154-159  收稿日期: 2020-12-01;收到修改稿日期: 2021-02-27
基金项目: 国家自然科学基金项目(51875482)
作者简介: 蒋宇涵（1995-），男，四川成都市人，硕士研究生，专业方向为机械设备故障诊断
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