Study of predicting breakdown voltage of stator insulation in generator based on BP neural network / 西安交通大学学报·英文版
Academic Journal of Xi'
; an Jiaotong University;(4): 34-37, 2007.
Article
de Zh
| WPRIM
| ID: wpr-844872
Bibliothèque responsable:
WPRO
ABSTRACT
The breakdown voltage plays an important role in evaluating residual life of stator insulation in generator. In this paper, we discussed BP neural network that was used to predict the breakdown voltage of stator insulation in generator of 300 MW/18 kV. At first the neural network has been trained by the samples that include the varieties of dielectric loss factor tanδ, the partial discharge parameters and breakdown voltage. Then we tried to predict the breakdown voltage of samples and stator insulations subjected to multi-stress aging by the trained neural network. We found that it's feasible and accurate to predict the voltage. This method can be applied to predict breakdown voltage of other generators which have the same insulation structure and material.
Texte intégral:
1
Indice:
WPRIM
Type d'étude:
Prognostic_studies
langue:
Zh
Texte intégral:
Academic Journal of Xi'an Jiaotong University
Année:
2007
Type:
Article