Title :
The use of moment features for recognition of partial discharges in generator stator winding models
Author :
Kai, Gao ; Kexiong, Tan ; Fuqi, Li ; Chengqi, Wu
Author_Institution :
Tsinghua Univ., Beijing, China
Abstract :
This contribution focuses on applying moment method on feature extraction and partial discharge (PD) discrimination. Four kinds of model bars are used to simulate typical partial discharges in generator stator winding. Moment features are calculated from the 3-d φ-q-n pattern charts. Back-propagation network (BP) is used to perform the recognition. The input vectors of BP network are formed in four ways: tabulated data, surface fitting parameters, moments and central moments. The effectivity of PD recognition with different kinds of input vectors is compared. The investigation shows that central moments have satisfactory ability in discriminating some typical types of PD in generator and in compressing the dimension of input characteristic vectors
Keywords :
backpropagation; electric generators; feature extraction; insulation testing; machine insulation; machine testing; method of moments; partial discharge measurement; pattern recognition; stators; backpropagation network; data tabulation; feature extraction; generator stator winding model; insulation diagnosis; moment method; partial discharge; pattern recognition; surface fitting; Bars; Dielectrics and electrical insulation; Fault location; Feature extraction; Moment methods; Partial discharges; Power system reliability; Stator windings; Surface discharges; Surface fitting;
Conference_Titel :
Properties and Applications of Dielectric Materials, 2000. Proceedings of the 6th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
0-7803-5459-1
DOI :
10.1109/ICPADM.2000.875688
