Title :
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.
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;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2005. IMTC 2005. Proceedings of the IEEE
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-7803-8879-8
DOI :
10.1109/IMTC.2005.1604558
