摘要
随着电力电子技术在低压领域的广泛应用,一些电器负载正常工作时的电压电流特性与故障电弧的典型特性相似,现有的小波变换故障检测方法难以区分故障电弧和特殊负载正常工作时的相似电弧,文章提出一种基于多分辨率分析的快速小波变换检测故障电弧的新方法。文中方法对负载电流采样数据运用Mallat算法进行多尺度分解,将重构后的小波高频系数的均值及差值作为判据,对多种类型的负载在故障和正常运行条件下的电流特性进行分析验证。结果表明:该检测方法能准确区分故障电弧和相似电弧,辨别特殊负载的能力增强,低压供配电系统中电弧故障断路器故障诊断的准确率提高。与现有方法相比,文中方法具有计算简单、诊断可靠性高等特点。
As the electric power ＆ electronic technology is used widely in low voltage area, the properties of voltage and current of some electrical loads in normal working conditions closely resemble or mimic the un-normal properties created by the arc fault. For the existing arc fault detection method based on wavelet transform is difficult to distinguish between fault arc and the similar arc generated by the special load during normal working, this paper proposes a new method of the fast wavelet transform based on multi-resolution analysis to detect fault arc. In this method, the sampling signal of loads current was decomposed to low and high frequency signals used the Mallat algorithm, and the mean and difference of the wavelet high frequency coefficients reconstructed were treated as the criteria for the fault detecting. The current of multiple types of loads working in normal or un-normal cases were analyzed in the experiment to verify the accuracy of the method. The experimental results show that, the detection method can distinguish between fault arc and similar arc accurately, the ability to identify specific loads were enhanced, and the diagnostic accuracy of the arc fault circuit interrupter used in low voltage power supply and distribution system was improved. Compared with the existing detection methods, this method is simple in calculation and has high diagnostic reliability.
出处
《山东建筑大学学报》
2014年第1期1-8,共8页
Journal of Shandong Jianzhu University
基金
国家自然科学基金项目(61374187)
关键词
故障电弧
小波高频系数
MALLAT算法
电弧故障断路器
干扰负载
fault arc
wavelet high frequency coefficients
Mallat algorithm
are fault circuit interruoter（AFCI） ： interference load
