Title
Research On Mechanical Fault Prediction Algorithm For Circuit Breaker Based On Sliding Time Window And Ann
Abstract
A new type of algorithm for predicting the mechanical faults of a vacuum circuit breaker (VCB) based on an artificial neural network (ANN) is proposed in this paper. There are two types of mechanical faults in a VCB: operation mechanism faults and tripping circuit faults. An angle displacement sensor is used to measure the main axle angle displacement which reflects the displacement of the moving contact, to obtain the state of the operation mechanism in the VCB, while a Hall current sensor is used to measure the trip coil current, which reflects the operation state of the tripping circuit. Then an ANN prediction algorithm based on a sliding time window is proposed in this paper and successfully used to predict mechanical faults in a VCB. The research results in this paper provide a theoretical basis for the realization of online monitoring and fault diagnosis of a VCB.
Year
DOI
Venue
2008
10.1093/ietele/e91-c.8.1299
IEICE TRANSACTIONS ON ELECTRONICS
Keywords
Field
DocType
vacuum circuit breaker, sliding time window, ANN (artificial neural network), mechanical fault prediction
Tripping,Hall effect sensor,Algorithm,Electronic engineering,Electromagnetic coil,Circuit breaker,Current sensor,Vacuum circuit breakers,Engineering,Artificial neural network,Axle,Electrical engineering
Journal
Volume
Issue
ISSN
E91C
8
1745-1353
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Xiaohua Wang11010.40
Mingzhe Rong279.56
Juan Qiu300.34
Dingxin Liu400.68
Biao Su500.34
Yi Wu613.44