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列车万向轴故障电机端识别方法研究

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动车组万向轴传动结构是转向架动力传输系统的动力传递装置,万向轴的动不平衡是高速列车运行品质和运行安全的关键.针对该问题提出了一种万向轴电机端动不平衡振动监测方法,首先通过长期的线路跟踪实验探索预警参数,进而建立时、频域振动预警模型;同时结合有限元仿真分析,模拟故障万向轴与正常万向轴之间的振动特征量关系,并结合大量实车数据统计分析得到故障万向轴的振动特征量;最后将得到的振动特征量用于设置万向轴故障阈值,建立万向轴故障判别标准,提出万向轴故障在线识别方法.利用实车故障万向轴的振动数据对提出的故障判别标准和识别方法进行验证.结果表明,基于实车数据统计定量分析和仿真定性分析得到的万向轴故障判别标准能准确地识别故障万向轴,其判别阈值合理,识别方法有效,具有一定的工程应用价值.
Study on Identification Method of Universal Joint Shaft Fault at the Motor End of Train
The cardan shaft transmission structure of EMU is the power transmission device of the bogie power transmission system.The dynamic unbalance of cardan shaft is the key to ensure the running quality and safety of high-speed trains.In order to solve this problem,a vibration monitoring method for the dynamic unbalance of the motor of the universal shaft is proposed.Firstly,the early-warning parameters are explored through long-term line tracking experiments,and then the vibration early-warning model in time and frequency domains is established.At the same time,through the finite element simulation analysis,the vibration characteristic quantity relationship between the faulty cardan shaft and the normal cardan shaft is simulated,and the vibration characteristic quantity of the faulty cardan shaft is obtained by the statistical analysis of a large number of real vehicle data.Finally,the vibration characteristics obtained are used to set the fault threshold of the cardan shaft,establish the fault identification standard of the cardan shaft,and propose the online fault identification method of the cardan shaft.The proposed fault discrimination standard and identification method are verified by using the vibration data of real vehicle fault cardan shaft.The results show that the cardan fault criterion based on statistical quantitative analysis of real vehicle data and qualitative analysis of simulation can accurately identify the fault cardan shaft within reasonable discrimination threshold,and the identification method proves effective,which holds practical engineering application value.

motoruniversal joint shaftdynamic unbalanceonline identificationsimulation analysis

凌元正、张兵

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西南交通大学 牵引动力国家重点实验室,四川 成都 610036

电机 万向轴 动不平衡 在线识别 仿真分析

国家重点研发计划

2017YFB1201103-06

2024

机械
四川省机械研究设计院 四川省机械工程学会 四川省机械科技情报标准研究所

机械

影响因子:0.392
ISSN:1006-0316
年,卷(期):2024.51(2)
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