DocumentCode :
2110664
Title :
Fault classification and fault signature production for rolling element bearings in electric machines
Author :
Stack, Jason R. ; Habetler, Thomas G. ; Harley, Ronald G.
Author_Institution :
US Naval Coastal Syst. Center, Panama City, FL, USA
fYear :
2003
fDate :
24-26 Aug. 2003
Firstpage :
172
Lastpage :
176
Abstract :
Most condition monitoring techniques for rolling element bearings are designed to detect the four characteristic fault frequencies. This has lead to the common practice of categorizing bearing faults according to fault location (i.e., inner race, outer race, ball, or cage fault). While the ability to detect the four characteristic fault frequencies is necessary, this approach neglects another important class of faults that arise in many industrial settings. This research introduces the notion of categorizing bearing faults as either single-point defects or generalized roughness. These classes separate bearing faults according to the types of fault signatures that are produced rather than by the physical location of the fault. Specifically, single-point defects produce the four predictable characteristic fault frequencies while faults categorized as generalized roughness produce unpredictable broadband changes in the machine vibration and stator current. Experimental results are provided from bearings failed in situ via a shaft current. These results illustrate the unpredictable and broadband nature of the effects produced by generalized roughness bearing faults. This issue is significant because a successful bearing condition monitoring scheme must be able to reliably detect both classes of faults.
Keywords :
condition monitoring; electric machines; failure analysis; fault diagnosis; machine bearings; vibrations; bearing faults; characteristic fault frequencies; condition monitoring; electric machines; fault classification; fault diagnosis; fault signature production; generalized roughness; machine vibration; rolling element bearings; shaft current; single-point defects; stator current; Condition monitoring; Electric machines; Electrical fault detection; Fault detection; Fault location; Frequency; Production; Rolling bearings; Shafts; Stators;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003. 4th IEEE International Symposium on
Print_ISBN :
0-7803-7838-5
Type :
conf
DOI :
10.1109/DEMPED.2003.1234568
Filename :
1234568
Link To Document :
بازگشت