Title :
Fault Diagnosis Method of High Voltage Circuit Breaker based on (RBF) Artificial Neural Network
Author :
Liu, Ai-Min ; Lin, Xin ; Liu, Xiang-Dong
Author_Institution :
Sch. of Electr. Eng., Shenyang Univ. of Technol.
Abstract :
In this paper a new fault diagnosis method of high voltage (HV) circuit breaker based on (RBF) artificial neural network theory is proposed. In addition, the paper presents a modified algorithm that aims at the defect that the method above cannot study new state type. Then the algorithm is employed in (HV) circuit breaker fault diagnosis. The modified algorithm can not only recognize the aware state but also recognize and find a brand new state type that has not been stored in the table of training sample. Last but not least it has the function of recognizing new state type
Keywords :
circuit breakers; fault diagnosis; neural nets; power system analysis computing; artificial neural network; fault diagnosis method; high voltage circuit breaker; Artificial neural networks; Circuit breakers; Circuit faults; Electrical fault detection; Fault diagnosis; Gaussian distribution; Neural networks; Pattern recognition; Transducers; Voltage; (RBF) neural network; artificial neural network; circuit breaker; confidence level; electric power system; fault diagnosis; mechanical fault; operation fault; state detection; state recognition;
Conference_Titel :
Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES
Conference_Location :
Dalian
Print_ISBN :
0-7803-9114-4
DOI :
10.1109/TDC.2005.1546925
