Test and prediction method for service life of bearing of axle box of train

Abstract

The invention provides a test and prediction method for a service life of a bearing of an axle box of a train. The method comprises: (1), sensors are arranged on a spring and a rotating arm of an axle box of a tested railway vehicle and the axle box is installed on the railway vehicle; (2), actual line testing of the vehicle for a distance is carried out and the operating speed and acceleration information are recorded, and a load-time process of a vertical load of the spring and a load-time process of a horizontal load of the rotating arm are collected; (3), a time process of an equivalent dynamic load of the bearing, the number of rotating turns of the bearing under a corresponding equivalent dynamic load, and the rated service-life turning number of the bearing under a corresponding equivalent dynamic load are calculated; and (4), on the basis of a Palmgren-miner linear damage accumulation rule, a predicted service life of the bearing is calculated. According to the invention, with the physical conception of the equivalent dynamic load-time process, linear accumulation of bearing damages within all data collection time intervals is carried out and thus the obtained predicted service life meets the actual situation well, so that the prediction accuracy is substantially improved.

Description

technical field [0001] The invention relates to an experimental prediction method for bearing life, in particular to an experimental prediction method for train axial bearing life. Background technique [0002] Bearings are the mechanical basic parts and core components of railway trains. Its quality directly affects the performance of trains. Correctly predicting the life of rolling bearings is the key to ensuring the normal operation of trains. At the same time, accurately predicting the fatigue life of railway bearings has always been a subject of concern to railway scholars and is difficult to solve. If the life of the bearing is predicted too large, it will cause a huge safety hazard. Once the bearing fails in advance, it will cause serious failures or accidents on the entire train; If the life of the bearing is estimated to be too small, resulting in premature replacement of the bearing, the disassembly process will greatly increase the maintenance cost, and at the sam...

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Problems solved by technology

At the same time, accurately predicting the fatigue life of railway bearings has always been a subject of concern to railway scholars and is difficult to solve. If the life of the bearing is predicted too large, it will cause a huge safety hazard. Once the bearing fails in advance, it will cause serious failures or accidents on the entire train; If the life of the bearing is estimated to be too small, resulting in premature replacement of the bearing, the disassembly process will greatly increase the maintenance cost, and at the same time cause a serious waste of high-quality resources

[0003] At present, the life prediction of railway bearings mainly adopts the traditional theoretical calculation method. The calculation method is aimed at the life prediction under constant load conditions. Complicated random loads are simply equivalent to dead loads or use correction coefficients to calculate life, which is not very accurate for the actual life prediction of high-speed rail bearings

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