摘要
针对超高压输电线路的超高速保护而建立人工神经网络模型,将输电线路行波信息和高频暂态电流信号经小波变换数据预处理,并提取相关时域和频域特征值之后作为分布式神经网络的输入,以通过人工神经网络来准确识别线路故障类型、故障位置,为实现保护的超高速动作提供判据。
Artificial neural network model is established for ultra-high speed protection on EHV transmission lines,we extract relevant time-domain and frequency domain characteristics to be a distributed neural network input after traveling wave information and high-frequency transient signals are pre-processed by wavelet transformation.The fault types and location on EHV transmission lines should be identified accurately through artificial neural network,then it can provide some protection criterion to achieve ultra-high-speed action.
出处
《四川理工学院学报（自然科学版）》
CAS
2010年第3期328-330,共3页
Journal of Sichuan University of Science & Engineering(Natural Science Edition)
基金
人工智能四川省高校重点实验室项目(2008RK009)
关键词
小波变换
行波信息
超高速保护
wavelet
traveling wave information
uitra-high speed protection
