Title :
Pattern recognition of PD in large turbine generators with a neural network system
Author :
Wu, Guangning ; Xie, Hengkun ; Ma, Hui ; Jiang, Xiongwei ; Chen, Zhiqing ; Sun, Delin
Author_Institution :
Xi´´an Jiaotong Univ., China
Abstract :
In this paper, a neural network system used for pattern recognition of partial discharge (PD) is described. The neural network is a three-layer artificial neural system with feed forward connections, and its learning method is back propagation algorithm incorporating with an external teacher signal. Digital PD pulse signal can be obtained by a PD pulse digitized record system. Combination of the discharge magnitude, the phase angle of applied voltage at which PD occurs, and the numbers of pulse counts are taken as the input of the neural network system. After learning typical input patterns, the neural network may discriminate unknown patterns successfully. Some new results are given, and practical application of neural network for pattern recognition of PD in large turbine generators is also discussed
Keywords :
backpropagation; feedforward neural nets; insulation testing; machine insulation; machine testing; partial discharges; pattern recognition; turbogenerators; backpropagation algorithm; digital PD pulse signal; external teacher; learning; partial discharge; pattern recognition; three-layer feed-forward artificial neural network; turbine generator; Dielectrics and electrical insulation; Intelligent networks; Multilayer perceptrons; Neural networks; Partial discharge measurement; Partial discharges; Pattern recognition; Power generation; Turbines; Voltage;
Conference_Titel :
Properties and Applications of Dielectric Materials, 1997., Proceedings of the 5th International Conference on
Conference_Location :
Seoul
Print_ISBN :
0-7803-2651-2
DOI :
10.1109/ICPADM.1997.617575