| 建筑配电系统故障电弧的仿真与检测 |
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| 引用本文： | 赵淑敏,吴为麟. 建筑配电系统故障电弧的仿真与检测[J]. 低压电器, 2007, 0(10): 38-42 |
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| 作者姓名： | 赵淑敏 吴为麟 |
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| 作者单位： | 浙江大学,电气工程学院,浙江,杭州,310027 |
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| 摘 要： | 选择合适的电弧模型,对建筑配电系统发生的故障电弧进行了仿真.基于小波的时一频分析特点和人工神经网络(ANN)的学习能力,提出了一种分辨故障电弧和正常负荷电流的方法.该方法通过小波变换对信号进行多分辨率分析,提取信号的特征矢量,利用人工神经网络对输入特征矢量进行故障识别.仿真实验的结果表明,该方法具有良好的故障识别件能.
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| 关 键 词： | 建筑配电系统 故障电弧 小波变换 人工神经网络 故障检测 |
| 文章编号： | 1001-5531（2007）10-0038-05 |
| 修稿时间： | 2007-03-12 |
Simulink and Detection of Fault Arcing for Building Power Distribution System |
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| ZHAO Shumin,WU Weilin. Simulink and Detection of Fault Arcing for Building Power Distribution System[J]. Low Voltage Apparatus, 2007, 0(10): 38-42 |
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| Authors: | ZHAO Shumin WU Weilin |
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| Affiliation: | College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China |
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| Abstract: | The model of arcing was selected to sumulink the fault arcing produced in building power distribution system.Based on time-frequency analysing character of wavelet and learning ability of artifical neural network(ANN),a method of dectecting fault arcing and normal load current was presented.The current signals were decomposed with wavelet transform multi-resolution analysis and the feature vectors were extracted.Then the ANN was used to achieve the automatic fault detection according to the input feature vectors.Test results showed that this method had good performance for fault detection. |
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| Keywords: | building power distribution system fault arcing wavelet transform artificial neural network(ANN) fault detection |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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