首页> 外文会议>International Conference on Mechanical Engineering and Technology >APPLICATION OF NEURAL NETWORKS IN FAULT CURRENT DETECTION
【24h】

APPLICATION OF NEURAL NETWORKS IN FAULT CURRENT DETECTION

机译:神经网络在故障电流检测中的应用

获取原文

摘要

In order to effectively achieve fault current detection for a hybrid circuit breaker, design a short-circuit current detection methods based on dynamic neural network, it applies the dynamic neural network to the fault current detection, uses historical memory effect of feedback neural networks to predict and compare the signals, can realize an effective short-circuit current fault detection. Using the Matlab neural network toolbox for simulation, simulation training samples generated by simulation, superpose multiphase harmonic components by single-phase fundamental frequency, similar sine function can be used instead when predigestion, the simulation results show that the method is effective and fast.
机译:为了有效地实现混合断路器的故障电流检测,设计基于动态神经网络的短路电流检测方法,将动态神经网络应用于故障电流检测,使用反馈神经网络的历史记忆效应来预测并比较信号,可以实现有效的短路电流故障检测。使用MATLAB神经网络工具箱进行仿真,模拟产生的仿真训练样本,通过单相频率叠加多相谐波分量,可以使用类似的正弦功能,而是在预见时,仿真结果表明该方法有效且快速。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号