The Application of the Fuzzy Neural Network-Wavelet Singularity Detection in Mechanical Fault Diagnosis of High Voltage Breakers

Author

Sun Laijun ; Xiaoguang, Hu ; Yanchao, Ji ; Chao, Lv

Author_Institution

Dept. of Electr. Eng., Harbin Inst. of Technol.

Volume

3

fYear

2005

fDate

16-19 May 2005

Firstpage

2164

Lastpage

2167

Abstract

In this paper, a new method that the wavelet singularity detecting and NN of fuzzy combined to process the mechanism libration signal of the HV breaker is introduced, which is called the NN of fuzzy singularity. This is a new method that the wavelet singularity exponent of fuzzification combined with the multilayer feedforward NN is imported to the mechanism fault diagnosis of the HV breaker. The experimental results show that this method can achieve better effect than the wavelet singularity detecting and improves the accuracy and precision of diagnosis

Keywords

circuit breakers; fault diagnosis; feedforward neural nets; fuzzy neural nets; signal detection; vibrations; wavelet transforms; fuzzy neural network; fuzzy singularity; high voltage breakers; mechanical fault diagnosis; mechanism libration signal; multilayer feedforward neural network; wavelet singularity detection; Electrical fault detection; Fault detection; Fault diagnosis; Frequency; Fuzzy neural networks; Intelligent networks; Neural networks; Signal analysis; Vibrations; Voltage; HV breaker; fault diagnosis; fuzzy neural network; neutral network; wavelet singularity;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE

Conference_Location

Ottawa, Ont.

Print_ISBN

0-7803-8879-8

Type

conf

DOI

10.1109/IMTC.2005.1604558

Filename

1604558