| 基于遗传算法优化小波神经网络的井下电缆故障测距方法 |
| |
| 引用本文： | 田书,赵敏. 基于遗传算法优化小波神经网络的井下电缆故障测距方法[J]. 煤矿机电, 2011, 0(6) |
| |
| 作者姓名： | 田书 赵敏 |
| |
| 作者单位： | 河南理工大学电气工程与自动化学院,河南焦作,454000 |
| |
| 摘 要： | 针对煤矿井下电网发生单相接地故障后定位困难,现有测距方法可靠性及测距精度低等问题,提出基于故障后暂态电气量由遗传算法优化小波神经网络,实现井下电缆馈线单相接地故障测距的方法。通过不同过渡电阻,故障距离情况的仿真结果表明,基于遗传算法优化的小波神经网络能实现准确故障测距,且较之基于BP算法小波神经网络的测距方法,其在测距精度和收敛时间方面表现更优。
|
| 关 键 词： | 故障测距 小波神经网络 遗传算法 |
Fault Location of Underground Cable Based on Genetic Algorithm Optimized Wavelet Neural Network |
| |
| TIAN Shu,ZHAO Min. Fault Location of Underground Cable Based on Genetic Algorithm Optimized Wavelet Neural Network[J]. Colliery Mechanical & Electrical Technology, 2011, 0(6) |
| |
| Authors: | TIAN Shu ZHAO Min |
| |
| Affiliation: | TIAN Shu,ZHAO Min(School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454000,China) |
| |
| Abstract: | According to the problems that difficult to position when single phase grounding fault happens at underground coal mine power cable and the low reliability and low distance measuring precious for existing distance measuring method,the genetic algorithm optimized wavelet neural network based on transient electric valve after fault is proposed,which realizes the method of underground coal mine cable single phase grounding fault distance measuring.Through different transition resistance,fault distance situatio... |
| |
| Keywords: | fault distance measuring wavelet neural network genetic algorithm |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
