DocumentCode
2470865
Title
General Regression Neural Networks as rotor fault detectors of the induction motor
Author
Kaminski, Marcin ; Kowalski, Czeslaw T. ; Orlowska-Kowalska, Teresa
Author_Institution
Inst. of Electr. Machines, Drives & Meas., Wroclaw Univ. of Technol., Wroclaw, Poland
fYear
2010
fDate
14-17 March 2010
Firstpage
1239
Lastpage
1244
Abstract
This paper presents the application of the General Regression Neural Networks in the diagnostics of the induction motors. The specific fault symptoms of rotor damages included in measured stator current spectrum are proposed as elements of input vectors of GRNN. The structure and training procedure of such neural detector are described. Diagnostic results obtained by the proposed neural detector of rotor faults are demonstrated.
Keywords
fault diagnosis; induction motor drives; neural nets; power engineering computing; regression analysis; rotors; general regression neural networks; induction motor drives; neural detector; rotor fault detectors; stator current spectrum; Detectors; Electrical fault detection; Fault detection; Frequency; Induction motors; Mathematical model; Neural networks; Rotors; Signal analysis; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology (ICIT), 2010 IEEE International Conference on
Conference_Location
Vi a del Mar
Print_ISBN
978-1-4244-5695-6
Electronic_ISBN
978-1-4244-5696-3
Type
conf
DOI
10.1109/ICIT.2010.5472618
Filename
5472618
Link To Document