Research of Health Diagnosis Strategy with Neural Network of Vacuum Circuit Breakers of 10 kV Switchgear
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摘要: 为了解决10 kV开关柜的真空断路器的维修不足和维修盲目等问题,在对真空断路器故障类型及征兆分析的基础上,提出了一种基于RBF神经网络的10 kV开关柜的真空断路器健康诊断策略。该策略通过传感器提取到真空断路器的特征参数,得到反映真空断路器健康状况的特征量,并以这些特征量作为RBF网络的输入,对真空断路器进行健康诊断,以达到提前预防的目的。Matlab仿真结果证明了该策略的有效性。Abstract: In order to solve problems of lack maintenance and blind repair existed in vacuum circuit breakers of 10 kV switchgear , the paper put forward a health diagnosis strategy of vacuum circuit breaker of 10 kV switchgear based on RBF neural network on basis of analysis of fault type and portent. The strategy uses sensor to extract characteristic parameters of vacuum breaker, obtains characteristic quantity of state of health, and takes these characteristic quantities as input of RBF network to diagnose health condition of vacuum circuit breaker, so as to achieve preventive goal. The simulation results by Matlab proved effectiveness of the strategy.
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