Title :
Artificial neural networks for recognition of 3-d partial discharge patterns
Author :
Satish, L. ; Zaengl, Walter S.
Author_Institution :
High Voltage Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland
fDate :
4/1/1994 12:00:00 AM
Abstract :
Partial discharge (PD) measurements have been carried out over the years to assess insulation systems in power apparatus for their integrity and design deficiencies. Digital PD recording, processing and its presentation as 3-d patterns are recent trends in both industry and testing laboratories. Interpretation of these patterns can lead to evaluation of the cause of PD. A need arises to look for methods in the domain of pattern recognition for automating this process. In this context, this paper presents results to demonstrate the possibility of using pattern recognition capabilities offered by a multilayer neural network to recognize 3-d PD patterns
Keywords :
feedforward neural nets; insulation testing; learning (artificial intelligence); partial discharges; pattern recognition; 3D partial discharge pattern recognition; artificial neural networks; digital PD recording; insulation system assessment; learning process; multilayer neural network; power apparatus; Artificial neural networks; Digital recording; Insulation; Laboratories; Multi-layer neural network; Partial discharge measurement; Partial discharges; Pattern recognition; Power measurement; Testing;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
