低频周期性晃车时频特性分析及快速诊断方法

doi:10.3901/JME.2024.18.318

机械工程学报 ›› 2024, Vol. 60 ›› Issue (18): 318-326.doi: 10.3901/JME.2024.18.318

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低频周期性晃车时频特性分析及快速诊断方法

解婉茹¹, 刘金朝¹, 赵钢², 孙丽霞³, 肖炳环⁴, 张茂轩¹

1. 中国铁道科学研究院集团有限公司基础设施检测研究所北京 100081;
2. 中国国家铁路集团有限公司铁路基础设施检测中心北京 100081;
3. 中国铁道科学研究院集团有限公司铁道科学技术研究发展中心北京 100081;
4. 中国铁道科学研究院研究生部北京 100081

收稿日期:2023-10-12 修回日期:2024-06-28 出版日期:2024-09-20 发布日期:2024-11-15
作者简介:解婉茹,女,1997年出生。主要研究方向为铁路基础设施检测数据分析。E-mail:xwr_1997@163.com
刘金朝(通信作者),男,1971年出生,博士,研究员,博士研究生导师。主要研究方向为基于车辆动态响应轨道状态评判和智能数据分析方法。E-mail:liujinzhao@rails.cn
基金资助:
中国铁道科学研究院集团有限公司科研项目重大课题(2019YJ153)。

Time Frequency Characteristic Analysis and Fast Diagnosis Method of Low Frequency Periodic Vehicle Body Hunting

XIE Wanru¹, LIU Jinzhao¹, ZHAO Gang², SUN Lixia³, XIAO Binghuan⁴, ZHANG Maoxuan¹

1. Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing 100081;
2. Infrastructure Inspection Center, China Railway, Beijing 100081;
3. Railway Science and Technology Research and Development Center, China Academy of Railway Sciences Corporation Limited, Beijing 100081;
4. Graduate Department, China Academy of Railway Sciences, Beijing 100081

Received:2023-10-12 Revised:2024-06-28 Online:2024-09-20 Published:2024-11-15

摘要/Abstract

摘要： 随着高速动车组运营速度不断提高，低频周期性晃车问题时有发生。快速有效识别出低频周期性晃车区段必要且迫切。依据低频周期性晃车成因，利用短时傅里叶变换，挖掘得到车辆响应数据的时频特性：车体横向振动主频十分接近车体上心滚摆频率、周期性强、能量大。在进行短时傅里叶变换计算时频谱的基础上，提出能够刻画低频周期性晃车特性的诊断指标：振动主频、振动强度因子和能量集中率。为提高计算效率，引入连续多波快速搜索算法，以车体横向加速度连续6波超过0.02 g为评判条件搜索获得同时包含晃车与少量未晃车区段的动态响应数据集合，结合诊断指标，形成能满足工程在线应用需求的低频周期性晃车快速诊断方法。利用新方法对大量实测的高速综合检测列车数据进行分析，结果表明该方法能够有效识别出低频周期性晃车。

关键词: 晃车诊断, 车体加速度, 蛇行运动, 连续多波

Abstract: With the continuous improvement of the operation speed of high-speed EMVS, the problem of low-frequency periodic hunting occurs from time to time. It is necessary and urgent to quickly and effectively identify the low frequency periodic shaking section. According to the causes of low-frequency periodic hunting, the time-frequency characteristics of vehicle response data are obtained by using short-time Fourier transform: the main frequency of lateral vibration of vehicle body is very close to the rolling pendulum frequency of upper center of vehicle body, with strong periodicity and high energy. On the basis of calculating the frequency marginal spectrum of short-time Fourier transform analysis, the diagnostic indexes which can describe the characteristics of low-frequency periodic car hunting are proposed: vibration dominant frequency, vibration degree factor and energy concentration rate. In order to improve the computational efficiency, a continuous multi wave fast search algorithm is introduced, and the dynamic response data set including hunting and a small number of non-hunting sections is obtained by taking the continuous 6-wave lateral acceleration of the car body more than 0.02g as the evaluation condition. Combined with the diagnosis index, a fast diagnosis method of low-frequency periodic hunting is formed, which can meet the needs of engineering online application. The results show that the method can effectively identify the low frequency periodic hunting.

Key words: vehicle body hunting diagnosis, vehicle acceleration, hunting motion, continuous multi-wave

中图分类号:

U216

解婉茹, 刘金朝, 赵钢, 孙丽霞, 肖炳环, 张茂轩. 低频周期性晃车时频特性分析及快速诊断方法[J]. 机械工程学报, 2024, 60(18): 318-326.

XIE Wanru, LIU Jinzhao, ZHAO Gang, SUN Lixia, XIAO Binghuan, ZHANG Maoxuan. Time Frequency Characteristic Analysis and Fast Diagnosis Method of Low Frequency Periodic Vehicle Body Hunting[J]. Journal of Mechanical Engineering, 2024, 60(18): 318-326.

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低频周期性晃车时频特性分析及快速诊断方法

Time Frequency Characteristic Analysis and Fast Diagnosis Method of Low Frequency Periodic Vehicle Body Hunting

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