Application of wavelet transform and EEMD in electromagnetic acoustic signal de-noising

Author

Peng Chen ; De-Lai Han ; Qiang-Fu Cai ; Hao Liu

Author_Institution

Ordnance Eng. Coll., Shijiazhuang, China

fYear

2013

fDate

15-18 July 2013

Firstpage

1734

Lastpage

1737

Abstract

The echo signal of electromagnetic acoustic detection have a small amplitude and a low SNR. By means of wavelet transform (WT) and ensemble empirical mode decomposition (EEMD), an electromagnetic acoustic echo signal was analyzed and the results show that both WT and EEMD are efficient ways for processing non-stationary signals. Conclusion can be made the EEMD is more adaptive than WT analysis in processing non-stationary signals. The EEMD method provides a new way in electromagnetic acoustic signal de-noising.

Keywords

acoustic signal detection; echo; signal denoising; wavelet transforms; EEMD; electromagnetic acoustic detection; electromagnetic acoustic echo signal; electromagnetic acoustic signal de-noising; ensemble empirical mode decomposition; nonstationary signal processing; wavelet transform; Acoustics; Electromagnetics; Noise; Signal resolution; Time-frequency analysis; Wavelet transforms; EEMD; electromagnetic acoustic; nondestructive testing; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-1014-4

Type

conf

DOI

10.1109/QR2MSE.2013.6625911

Filename

6625911