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高速列车轴箱轴承多故障滚动体振动模型及其缺陷定位方法 被引量:2

Vibration model for axle box bearings with multiple defective rolling elements for high-speed trains and the defects localization method
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摘要 针对传统时域分析方法识别滚动轴承故障滚动体数量和相位信息容易失效的问题,建立了存在多个故障滚动体的滚动轴承振动模型,并提出了基于包络谱和卷积平均思想的故障滚动体定位方法。所提模型综合考虑了包括轴承几何结构、轴转速、轴承载荷分布、传递函数、振动的指数衰减和滚动体随机滑动等多个因素。结合所提模型,推导出不同滚动体缺陷激发的最大冲击的时间间隔受缺陷在滚动体上的位置分布的影响,导致该时间间隔存在较大波动。阐述了传统时域分析中,采用最大冲击间隔定位故障滚动体容易失效的原因。应用高速列车轴箱轴承试验数据验证了所提模型的准确性和所提缺陷定位方法的有效性,结果表明,所提模型对理解滚动体故障轴承的振动机理和对设计具体的分析和诊断工具有所帮助,所提缺陷定位方法能有效识别故障滚动体的数量和间隔信息,相比传统时域分析方法,缺陷定位的效率和抗噪声干扰能力得到了显著提高。 Aiming at improving the shortcomings of the traditional time-domain analysis method for locating defective rolling elements,a vibration model for rolling bearings with multiple defective rolling elements was established,and then a defects localization method based on envelope spectrum and convolution average was proposed.The effects of bearing geometry,shaft speed,bearing load distribution,transfer function,exponential decay of vibration and the random slip of rolling elements and cage were taken into account in the vibration model.Making use of the model,it is found that the time interval between the maximum impulses produced by different rolling element defects is affected by the position distribution of defects on rolling elements.The invalidation of the traditional time-domain analysis method in some cases was explored and then explained.The test data of high-speed train axle box bearings were used to verify the accuracy of the proposed model and the effectiveness of the proposed defects localization method.The results show that the proposed model is helpful to understand the vibration mechanism of faulty bearings and to design specific analysis diagnostic tools.The proposed defects localization method can effectively identify the number and interval information of the defective rolling elements.Comparing with the traditional time-domain analysis method,the efficiency of defects localization and the ability to resist noise are significantly improved.
作者 黄晨光 张兵 易彩 靳行 HUANG Chenguang;ZHANG Bing;YI Cai;JIN Hang(State Key Laboratory of Traction Power,Southwest Jiaotong University,Chengdu 610031,China;Big Data Department,Weichai Power Co.,Ltd.,Weifang 261000,China)
出处 《振动与冲击》 EI CSCD 北大核心 2020年第18期34-43,共10页 Journal of Vibration and Shock
基金 国家重点研发计划资助(2016YFB1200401-102) 国家科技计划项目(2017YFB1201103-06)。
关键词 轴箱轴承 振动模型 多故障滚动体 缺陷定位 卷积平均 axle box bearing vibration model multiple defective rolling elements defect localization convolution average
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