Title :
A rotor fault intelligence diagnosis system based on virtual instrument
Author :
An Guoqing ; Liu Donghui ; Zhu Weilu ; Sun Kejun
Author_Institution :
Sch. of Electr. Eng., Hebei Univ. of Technol., Tianjin, China
Abstract :
In order to get the rotor fault characteristic component in stator current, an advanced correlation algorithm is presented in this paper. Because of faster and multi-channel ADC subsystem, S3C2410 ARM is chosen as the core of stator current acquisition to meet the need of spectrum analysis. By programming on LabWindows/CVI - a virtual instrument development tool, the fault information can be separated from stator current signal. Then make the spectrum analysis to the residual signal, the broken bar fault can be diagnosed easily. The results of experiment indicate that a reliable and portable system can be realized to meet the purpose of testing and diagnosing the faults of induction motors in-situation, and method is feasible and effective.
Keywords :
analogue-digital conversion; fault diagnosis; induction motors; microcontrollers; power engineering computing; rotors; stators; virtual instrumentation; LabWindows-CVI; S3C2410 ARM; advanced correlation algorithm; broken bar fault; multichannel ADC subsystem; rotor fault intelligence diagnosis system; spectrum analysis; stator current acquisition; virtual instrument development tool; Circuit faults; Correlation; Induction motors; Instruments; Rotors; Stator cores; ARM; intelligent diagnosis; rotor fault; virtual instrument;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6022847
