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| 支持向量机的低压故障电弧识别方法 | |
| 引用本文： | 徐贞华. 支持向量机的低压故障电弧识别方法[J]. 电力系统及其自动化学报, 2012, 24(2): 128-131 |
| 作者姓名： | 徐贞华 |
| 作者单位： | 江西铜业股份有限公司德兴铜矿动力厂,德兴,334224 |
| 摘 要： | 故障电弧是引发电气火灾事故的主要原因之一。该文将支持向量机引入故障电弧研究领域,进行不同负荷情况下故障电弧识别检测。首先参照美国UL1699标准进行实验采集电流数据,然后利用支持向量机实现故障电弧训练、检测识别,并对训练、识别结果进行分析,实验证明本文的检测方法具备一定的泛化能力。 |
| 关 键 词： | 支持向量机 核函数 故障电弧 |
Detection of Low-voltage Arc Fault Based on Support Vector Machine |
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| XU Zhen-hua. Detection of Low-voltage Arc Fault Based on Support Vector Machine[J]. Proceedings of the CSU-EPSA, 2012, 24(2): 128-131 | |
| Authors: | XU Zhen-hua |
| Affiliation: | XU Zhen-hua(Dexing Copper Mine Power Plant,Jiangxi Copper Company Limited, Dexing 334224,China) |
| Abstract: | Arc fault is one of the prime reasons causing electrical fire accidents.In this paper,the support vector machine(SVM)is applied to the field of arc faults,for the prupose of detecting arc faults under different loads.Firstly,experiment data are collected based on UL1699.Arc faults are detected and identified by applying SVM.The analysis of the results shows that this detection method has some generalization. |
| Keywords: | support vector machine(SVM) kernal function arc fault |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |