Signal processing techniques for rolling element bearing spall size estimation

2019 ◽  
Vol 117 ◽  
pp. 16-32 ◽  
Author(s):  
Aoyu Chen ◽  
Thomas R. Kurfess
Keyword(s):  
Signal Processing ◽  
Rolling Element Bearing ◽  
Size Estimation ◽  
Rolling Element ◽  
Element Bearing ◽  
Processing Techniques ◽  
Signal Processing Techniques

Diagnostics of Rolling Element Bearings for the Traction System of High Speed Trains: Experimental Evidences

2013 ◽  
Author(s):  
S. Chatterton ◽  
P. Pennacchi ◽  
R. Ricci ◽  
P. Borghesani
Keyword(s):  
Signal Processing ◽  
High Speed ◽  
Rolling Element Bearings ◽  
High Speed Train ◽  
Term Operation ◽  
Rolling Element ◽  
High Speed Trains ◽  
Traction System ◽  
Processing Techniques ◽  
Signal Processing Techniques

Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.

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