| 基于RBF神经网络的无通道保护 |
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| 引用本文： | 陈少华,余耀权,郑帅,叶杰宏.基于RBF神经网络的无通道保护[J].福建工程学院学报,2004,2(2):134-137,148. |
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| 作者姓名： | 陈少华 余耀权 郑帅 叶杰宏 |
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| 作者单位： | 广东工业大学自动化学院,广东,广州,510090 |
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| 基金项目： | 广东省教育厅自然科学基金(Z02033) |
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| 摘 要： | 在故障分析的基础上，阐述了应用径向基函数神经网络(RBF神经网络)实现输电线全线路无通道快速保护的原理，并对各种故障类型的电磁暂态分析程序(EMTP)和madab进行仿真测试，以证明该保护的可行性。
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| 关 键 词： | 电流保护 无通道保护 RBF神经网络 相继动作 |
| 文章编号： | 1672-4348(2004)02-0134-04 |
| 修稿时间： | 2004年4月30日 |
Non- communication protection based on RBF neural network |
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| CHEN Shao-hua,YU Yao-quan,ZHENG Shuai,YE Jie-hong.Non- communication protection based on RBF neural network[J].Journal of Fujian University of Technology,2004,2(2):134-137,148. |
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| Authors: | CHEN Shao-hua YU Yao-quan ZHENG Shuai YE Jie-hong |
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| Abstract: | On the basis of fault analysis, this paper describes the principle of non-communication fast protection of a whole transmission line with artificial neural network, the protection consisting of two parts: instantaneous protection within the protective range of 85% and successive tripping protection beyond the protective range of 85%. The network, a three-layered RBF model, consists of four subsidiary networks: ANN1 to determine fault directions, ANN2 to identify fault types and fault phase, ANN3 to trip breaker instantaneously and ANN4 to detect tripping situation of an adjacent breaker. Simulation results of all types of faults demonstrate that the model is feasible. |
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| Keywords: | current protection non-communication protection RBF neural network succesive tripping |
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