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基于小波神经网络的电缆故障定位研究

Study of Faulted Location of Cable Line Based On Wavelet Network
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摘要 为了实现电缆故障在线定位,通过对故障特征分析,得出发生故障的暂态信号中含有丰富的暂态高频信号,且暂态高频信号与故障距离成一定的映射关系。本文利用小波包理论提取故障暂态特征信号的小波包系数,充分利用神经网络的非线性函数拟合功能实现小波包系数到故障距离的映射,解决故障在线测距。仿真结果表明,利用此方法可以有效地实现故障定位。 In order to achieve the fault-line cable position,this paper analyzes the characteristics of the fault and finds that the transient signal contains a wealth of high-frequency transient signal,and high-frequency transient signal failures and a certain distance has the mapping relations.In this paper,wavelet packet theory is used to extract the fault transient signal characteristics of the wavelet packet factor,and the neural networks nonlinear function is used to achieve the mapping between the coefficients of wavelet packet and the failure distance,by this method,the failure on-line location is realized.The simulation results show that this method can be effective in fault location.
作者 闫晓茹
出处 《机电工程技术》 2009年第4期97-100,共4页 Mechanical & Electrical Engineering Technology
关键词 电缆故障 小波神经网 故障定位 faulted cable wavelet neural networks fault location
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