Research on Mechanical Fault Prediction Algorithm for Circuit Breaker Based on Sliding Time Window and ANN

Xiaohua WANG  Mingzhe RONG  Juan QIU  Dingxin LIU  Biao SU  Yi WU  

IEICE TRANSACTIONS on Electronics   Vol.E91-C   No.8   pp.1299-1305
Publication Date: 2008/08/01
Online ISSN: 1745-1353
DOI: 10.1093/ietele/e91-c.8.1299
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Recent Development of Electromechanical Devices(Selected Papers from IS-EMD2007))
Category: Contactors & Circuit Breakers
vacuum circuit breaker,  sliding time window,  ANN (artificial neural network),  mechanical fault prediction,  

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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.