A study of surface partial discharge patterns relevant to the endurance of polymer films by means of a neural network

2002 ◽  
Author(s):  
L. Centurioni ◽  
R. Bozzo ◽  
C. Gemme ◽  
F. Guastavino
Keyword(s):  
Neural Network ◽  
Polymer Films ◽  
Partial Discharge ◽  
Discharge Patterns

scholarly journals GIS Partial Discharge Patterns Recognition with Spherical Convolutional Neural Network

2020 ◽  
Vol 853 ◽  
pp. 012001
Author(s):  
Wei Yang ◽  
Guobao Zhang ◽  
Taiyun Zhu ◽  
Mengyi Cai ◽  
Hengyang Zhao ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Partial Discharge ◽  
Discharge Patterns

A COMPOSITE PROBABILISTIC NEURAL NETWORK SYSTEM FOR PD PATTERN RECOGNITION

2005 ◽  
Vol 02 (02) ◽  
pp. 149-165 ◽  
Author(s):  
B. KARTHIKEYAN ◽  
S. GOPAL ◽  
M. VIMALA
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Network Architecture ◽  
Probabilistic Neural Network ◽  
Partial Discharge ◽  
Network System ◽  
Knowledge Based ◽  
Neural Network System ◽  
Insulation Systems ◽  
Discharge Patterns

Partial discharge patterns are an important tool for diagnosis of HV insulation systems. Skilled humans can identify the possible insulation defects in various representations of partial discharge (PD) data. One of the most widely used representation is phase resolved PD (PRPD) patterns. This paper describes a method for the automated recognition of PRPD patterns using a novel composite neural network system for the actual classification task. This paper elucidates the possible methods of extracting relevant features from the PRPD data in a knowledge based way i.e. according to physical properties of PD gained from PD modeling. This allows the novel complex neural network (NN) system for classification. The efficacy of composite neural network developed using original probabilistic neural network is examined. This innovative methodology of giving inputs to the composite neural network compares favorably with the traditional network architecture used previously for PD pattern recognition.

Discrimination of partial discharge patterns using a neural network

1992 ◽  
Vol 27 (3) ◽  
pp. 550-556 ◽  
Author(s):  
N. Hozumi ◽  
T. Okamoto ◽  
T. Imajo
Keyword(s):  
Neural Network ◽  
Partial Discharge ◽  
Discharge Patterns
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