Time-Frequency Analysis of Electrostatic Discharge Signal Based on Wavelet Transform

被引：0

作者：

Cheng, Cong ^{[1
]}

Ruan, Fangming ^{[1
,2
]}

Deng, Di ^{[3
]}

Li, Jia ^{[4
]}

Su, Ming ^{[2
]}

Pommerenke, David ^{[5
]}

机构：

[1] Guizhou Univ, Sch Big Data & Informat Engn, Guiyang, Guizhou, Peoples R China

[2] Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang, Guizhou, Peoples R China

[3] Guizhou Prov Inst Monitoring & Detecting Qual Mac, Guiyang, Guizhou, Peoples R China

[4] Shenzhen Zhenhuafu Elect Corp Co Ltd, Shenzhen, Peoples R China

[5] Missouri Univ Sci & Tech, EMC Lab, Rolla, MO USA

来源：

PROCEEDINGS OF 2018 12TH IEEE INTERNATIONAL CONFERENCE ON ANTI-COUNTERFEITING, SECURITY, AND IDENTIFICATION (ASID) | 2018年

关键词：

Electrostatic discharge; Wavelet transform; Time-frequency analysis;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Electrostatic discharge signal is a non-stationary signal whose frequency is varied with time. Time-frequency analysis is able to reveal the more useful information hidden in the ESD signal. In this letter, we propose a time-frequency analysis approach using the wavelet transform. Based on the Morlet wavelet, this paper analyzes the actual ESD signal and obtains its time-frequency characteristic. 2-D and 3-D ESD data are showed in this paper. The result shown that high frequency component of ESD can reach 0.6GHz. In addition, the energy of the measured signal is mainly concentrated in the range of 100 to 200 MHz. The high-frequency component attenuations rapidly and the low-frequency duration is relatively long. It can provide some new idea for extraction or signal denoising.

引用

页码：35 / 38

页数：4

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