Title :
Partial discharge pattern recognition for four kinds of electrode systems
Author :
Okamoto, Tatsuki ; Hozumi, Naohiro ; Imajo, Takahisa
Author_Institution :
Central Res. Inst. of Electr. Power Ind., Yokosuka, Japan
Abstract :
The authors describe a method for recognizing partial discharge characteristics for four kinds of electrode systems. The method uses a neural network system with an input of φ-q-n distribution patterns. The θ-q-n distribution consists of the pulse count n versus the pulse height q and the phase angle φ. The learning characteristics and recognition characteristics of the neural network were investigated, and the recognition capability for a combined pattern signal input was shown. The effectiveness of the neural network system for partial discharge recognition is discussed
Keywords :
backpropagation; electrical engineering computing; feedforward neural nets; image recognition; insulation testing; partial discharges; combined pattern signal input; error backpropagation method; learning characteristics; neural network system; partial discharge characteristics; pattern recognition; phase angle; pulse count; pulse height; recognition capability; Character recognition; Data processing; Electrodes; Neural networks; Partial discharge measurement; Partial discharges; Pattern recognition; Signal analysis; Signal processing; Voltage;
Conference_Titel :
Electrical Insulation, Conference Record of the 1992 IEEE International Symposium on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0649-X
DOI :
10.1109/ELINSL.1992.246985
