The Application of Multi-Sensor Data Fusion Technology in Partial Discharge Detector

Author

Juan, Wang ; Shuguang, Zhang ; Shan, Zhang ; Feng, Bao

Author_Institution

Dept. of Mech. & Electron. Eng., Agric. Univ. of Hebei, Baoding, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

The design of the hardware structure of the transformer partial discharge detector, based on data fusion technology, is proposed. The ultrasonic method and ultra-high frequency method are combined effectively. Genetic algorithm and neural network technology are explored in the transformer partial discharge detector. The system can detect partial discharge effectively, recognize the discharge pattern, position the discharge points, determine the discharge capacity and discharge repetition rate. It has broad application prospects.

Keywords

electric breakdown; genetic algorithms; neural nets; partial discharges; pattern recognition; power engineering computing; sensor fusion; discharge pattern recognition; genetic algorithm; multisensor data fusion technology; neural network technology; transformer partial discharge detector; ultrahigh frequency method; ultrasonic method; Circuits; Data acquisition; Detectors; Frequency conversion; Hardware; Optical amplifiers; Partial discharges; Power system stability; Power transformer insulation; Power transformers; Data fusion technology; Partial Discharge Detection; Pattern Recognition Introduction; Ultra-high frequency; Ultrasonic wave;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5367166

Filename

5367166