Title :
Fault Diagnosis of Induction Motor using Neural Networks
Author :
He, Qing ; Du, Dong-mei
Author_Institution :
North China Electr. Power Univ., Beijing
Abstract :
The fault diagnosis theory and its methods for inductor motor are summarized. Based on the method of current spectrum, a neural network method to diagnose the broken bar number of inductor motor is presented. The training patterns and the diagnosis results for the neural network are given. The broken bar number of inductor motor is diagnosed directly according to the working status parameters. The method is high intelligent and very reliable.
Keywords :
fault diagnosis; induction motors; neural nets; broken bar number; current spectrum; fault diagnosis; induction motor; neural networks; Circuit faults; Electric motors; Fault diagnosis; Frequency; Induction motors; Inductors; Magnetic flux; Neural networks; Rotors; Stator windings; Broken bar; Fault diagnosis; Induction motor; Neural networks;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370306
