Research on Monitoring System of Circuit Breakers Based on Neural Networks

Q1 Social Sciences HumanMachine Communication Journal Pub Date : 2010-04-24 DOI:10.1109/MVHI.2010.194
Yimin Hou, Tao Liu, Xiangmin Lun, Jianjun Lan, Yang Cui
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引用次数: 3

Abstract

The paper proposed a monitoring system for the circuit breakers in the substation based on the Back Propagation Neural Networks(BPNN). The novel temperature and humidity sensor was used in the system to get temperature and humidity value in the breakers. The carbon resistor displacement sensor was employed to get the displacement data of the contact in the closing or breaking procedure. All the data was transferred into the BPNN to obtain the remainder service life of the breakers set and give an alarm for the malfunction. In the experiments, the parameters were measured and the results showed that the system in this paper was efficient.
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基于神经网络的断路器监测系统研究
提出了一种基于反向传播神经网络(BPNN)的变电站断路器监控系统。该系统采用了新型温湿度传感器来获取断路器内的温湿度值。采用碳电阻位移传感器获取触点闭合或断开过程中的位移数据。将所有数据传输到BPNN中,得到断路器的剩余使用寿命,并对断路器的故障进行报警。在实验中,对系统参数进行了测量,结果表明了系统的有效性。
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来源期刊
CiteScore
10.00
自引率
0.00%
发文量
10
审稿时长
8 weeks
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