The new method on rotor winding inter turn short-circuit fault measure of turbine generator

Author(s):  
Li yonggang ◽  
Zhao hua ◽  
Li heming
2013 ◽  
Vol 427-429 ◽  
pp. 230-234
Author(s):  
Wen Jing Zhang ◽  
Yong Gang Li ◽  
Yu Ca Wu

Inter turn short circuit fault is very common for turbine-generator, which will produce unbalanced electromagnetic force (UEMF) together with its relevant fault, namely dynamic eccentric, on the rotor. After complete finite element simulation by ANSYS, The relationship of rotor winding short positions and short degrees with UEMF were studied. And then, only the dynamic eccentric fault occurs, the relations of dynamic eccentric angles and dynamic eccentric degrees with UEMF were discussed as well. Whats more, by comprehensive consideration of the two faults, the characteristic of the force and its change law were researched. This paper provides a viable path to study the vibration law and fault diagnosis of turbine-generator in multi-source stress.


2011 ◽  
Vol 143-144 ◽  
pp. 125-131 ◽  
Author(s):  
Yong Gang Li ◽  
Guo Wei Zhou ◽  
Yu Ca Wu ◽  
He Ming Li

This paper analyzes the calculation method of unbalanced electromagnetic force by rotor winding inter-turn short-circuit fault, analytical calculating method neglects saturation, cogging and other factors, so the calculation accuracy is not high, in order to accurately calculate the magnetic field and the unbalanced electromagnetic force, this paper propose to analyze generator magnetic field by a finite element software Ansys, the obtained magnetic field data are further used to analyze the distributed electromagnetic force and the total force that generator rotor suffered, electromagnetic force distribution law of different slots, different levels of inter-turn short-circuit are got, which provide a basis for further studying the full force on generator rotor.


2014 ◽  
Vol 543-547 ◽  
pp. 1064-1067
Author(s):  
Jian Qun Zhang ◽  
De Jian Zhou

As a common fault of motor, the short circuit of rotor winding is important for the accurate diagnosis. In this article, the author collected every status parameter of motor by different sensors, using two BP neural networks to partly diagnose the motor and fusing the results of partly diagnosis by D-S evidence theory. The author increases the creditability of diagnosis results by practices and decreases uncertainty, showing the efficiency of this method.


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