利用小波包树有效估计聚类高次谐波

I. Nicolae, P. Nicolae, Dusan Kostic, Daniel-Nicolae Cîrstea
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引用次数: 0

摘要

本研究讨论了7级小波包树(WPT)相对于快速估计频率高于2kHz的振荡分量的联合谐波贡献的能力。从树的根节点分析的信号跨越7个周期,以产生不受边缘效应影响的结果。从第7层开始连接节点的集群和相关的谐波被推导出来,以及要使用的标志,例如获得专用于每个集群的子树,以节省运行时间。分别对谐波含量丰富的人工信号和单簇谐波信号进行了测试。性能指标分析表明,6个聚类可用于估计超过2kHz的谐波贡献,最高可达4.25 kHz,同时考虑单个奇次谐波出现在其相关节点簇外的能量最多为2.5%的阈值。给出了罗马尼亚机车辅助变换器输出电压的算法应用实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Wavelet Packet Trees to Efficiently Estimate Clustered High Order Harmonics
This study deals with the capabilities of a 7 level Wavelet Packet tree (WPT) relative to fast estimation of joint harmonic contributions of components oscillating with frequencies higher than 2kHz. The analyzed signal from the tree’s root node spans across 7 periods such as to yield results unaffected by the edge effect. Clusters connecting nodes from the 7-th level and associated harmonics are deduced, along with flags to be used such as to obtain subtrees dedicated to each cluster for runtime savings. Tests on artificial signals with rich harmonic content and respectively with harmonics from a single cluster were made. The analysis of performance metrics revealed that 6 clusters can be used for the estimation of contributions of harmonic exceeding 2kHz, up to the limit of 4.25 kHz, while considering a threshold of at most 2.5% for the energy of individual odd harmonics to appear outside their associated cluster of nodes. An example of algorithm utilization for the output voltage of an auxiliary services converter used on a Romanian locomotive is provided.
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