As an important component of the running gear of high-speed trains,axle box bearings can cause lubricating grease failure and damage to bearing components under continuous high-temperature operation,which will affect ...As an important component of the running gear of high-speed trains,axle box bearings can cause lubricating grease failure and damage to bearing components under continuous high-temperature operation,which will affect the normal operation of highspeed trains.Therefore,bearing temperature is one of the key parameters to be monitored in the online monitoring system for trains.Based on the thermal network method,this paper establishes a thermal network model for the axle box bearing,considering the radial thermal deformation of the double-row tapered roller bearing components caused by the oil film characteristics and the temperature variations of the lubricating grease.A thermo-mechanical coupling model for the grease-lubricated double-row tapered roller axle box bearing of high-speed trains with track irregularity excitation is established.The correctness of the model is verified using the test bench data,and the temperature of the bearing at different rotational speeds,loads,fault sizes,and ambient temperatures are investigated.展开更多
High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in...High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.12393780,12032017,and 12002221)the Key Scientific Research Projects of China Railway Group(No.N2021J032)+2 种基金the College Education Scientific Research Project of Hebei Province of China(No.JZX2024006)the S&T Program of Hebei Province of China(No.21567622H)the National Scholarship Council of China。
文摘As an important component of the running gear of high-speed trains,axle box bearings can cause lubricating grease failure and damage to bearing components under continuous high-temperature operation,which will affect the normal operation of highspeed trains.Therefore,bearing temperature is one of the key parameters to be monitored in the online monitoring system for trains.Based on the thermal network method,this paper establishes a thermal network model for the axle box bearing,considering the radial thermal deformation of the double-row tapered roller bearing components caused by the oil film characteristics and the temperature variations of the lubricating grease.A thermo-mechanical coupling model for the grease-lubricated double-row tapered roller axle box bearing of high-speed trains with track irregularity excitation is established.The correctness of the model is verified using the test bench data,and the temperature of the bearing at different rotational speeds,loads,fault sizes,and ambient temperatures are investigated.
基金National Key R&D Program(Grant No.2020YFB2007700),National Natural Science Foundation of China(Grant Nos.11790282,12032017,12002221 and 11872256)S&T Program of Hebei(Grant No.20310803D)+1 种基金Natural Science Foundation of Hebei Province(Grant No.A2020210028)State Foundation for Studying Abroad.
文摘High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.