TY - JOUR
T1 - Partial discharge pattern recognition for three kinds of model electrodes with a neural network
AU - Okamoto, T.
AU - Tanaka, T.
PY - 1995/1/1
Y1 - 1995/1/1
N2 - The paper describes a method of recognizing partial discharge characteristics for three kinds of electrode systems. The method uses a neural network system with input signal of φ-q-n distribution patterns. The φ-q-n distribution consists of the pulse count [n] versus pulse height [q] and phase angle [φ]. The learning characteristics and recognition characteristics of the neural network were investigated. The basic characteristics of recognition capability for combined pattern signal input was shown. The effectiveness of the neural network system for partial discharge recognition was shown.
AB - The paper describes a method of recognizing partial discharge characteristics for three kinds of electrode systems. The method uses a neural network system with input signal of φ-q-n distribution patterns. The φ-q-n distribution consists of the pulse count [n] versus pulse height [q] and phase angle [φ]. The learning characteristics and recognition characteristics of the neural network were investigated. The basic characteristics of recognition capability for combined pattern signal input was shown. The effectiveness of the neural network system for partial discharge recognition was shown.
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U2 - 10.1049/ip-smt:19951430
DO - 10.1049/ip-smt:19951430
M3 - Article
AN - SCOPUS:0029232430
SN - 1350-2344
VL - 142
SP - 75
EP - 84
JO - IEE Proceedings: Science, Measurement and Technology
JF - IEE Proceedings: Science, Measurement and Technology
IS - 1
ER -