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논문검색

An Improved Spatially Selective Noise Filtration for Real-time Denoising of Acoustic Emission Signal

초록

영어

The denoising of acoustic emission (AE) signal plays an important role in structural health monitoring. This paper proposes the improved spatially selective noise filtration (SSNF) which can eliminate the Gaussian white noise well. Firstly, through the comparison of different vanishing moments, “db5” is chose as the mother wavelet. And the Mallat algorithm is used in the composition and reconstruction of signal processing. Secondly, according to the signal noise ratio of wavelet reconstructed coefficients of AE signal, two coefficients are chosen to the next step. Lastly, the denoising algorithm uses the high degree of correlation between coefficients to realize the improved SSNF. Compared with the SSNF, the improved SSNF can avoid “glitches” and realize real-time denoising. And according to the simulation results, the improved SSNF can realize real-time denoising of AE signal.

목차

Abstract
 1. Introduction
 2. Acoustic Emission
 3. Wavelet Transform
  3.1. Mallat Algorithm
  3.2. Vanishing Moments of Wavelet
 4. Improved Spatially Selective Noise Filtration
  4.1. Basical Spatially Selective Noise Filtration
  4.2. Improved Spatially Selective Noise Filtration
 5. Simulation Results and Analyses
 6. Conclusions
 Acknowledgements
 References

저자정보

  • Jian Wang School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, Weihai, 264209, China
  • Guangming Li School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, Weihai, 264209, China
  • Peng Sun School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, Weihai, 264209, China
  • Ruijuan Jiang Shenzhen Municipal Design & Research Institute Co., Ltd., Shenzhen, 518029, China
  • Yiyan Chen Shenzhen Municipal Design & Research Institute Co., Ltd., Shenzhen, 518029, China

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