Time-Frequency Ridge Analysis using on distinguish regular signal from arc-fault signal

被引：0

作者：

Pan, JunJie ^{[2
]}

Zhu, HongWei ^{[1
]}

Chen, LiSheng ^{[2
]}

机构：

[1] Zhejiang Univ, Inst VLSI Design, Hangzhou 310003, Zhejiang, Peoples R China

[2] Zhejiang Univ, Coll Elect Engn, Hangzhou 310003, Zhejiang, Peoples R China

来源：

2013 IEEE INTERNATIONAL WORKSHOP ON INTELLIGENT ENERGY SYSTEMS (IWIES) | 2013年

关键词：

harmonic analysis; chaos; regularity; Electrical fault detection; time-frequency analysis; instantaneous frequency; time-frequency ridges; spectrogram; WAVELET TRANSFORM; SYSTEM;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In the past decade, electronic devices are widely used in power supply system. They produce harmonic waveforms which look like chaos. Though a chaotic signal would be caused by arc-fault, it doesn't contain harmonic signal which is regular in nature. Conventional arc detection method failed to distinguish the harmonic signal from the chaotic signal, and the harmonic signal is judged as fault signal. This is because the conventional method analyzes signal solely on time or frequency domain, it losses information from the other domain. In this paper, a novel analytical methodology to distinguish regular signal from real chaos by making use of time-frequency ridges is proposed. This method is based on the knowledge that the non-fault electric signal has a highly regular time-frequency structure and its instantaneous frequency has a regular and stable representation; while the arc-fault doesn't has such properties. What's more, the method based on time-frequency ridges not only offers an effective way to represent instantaneous frequency but also is robust to noise and interference after some processing.

引用

页码：203 / 208

页数：6

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