Study on Denoising of Corrosion Acoustic Emission Signals of Tank Bottom Based on Independent Component Analysis

Abstract:

When tank bottom is detected by acoustic emission method, many corrosion acoustic emission signals can be obtained and adulterated many noise signals, which influence badly the estimation to the corrosion situation of tank bottom. In order to identify acoustic emission sources and disturbance sources without changing the characterization of acoustic emission sources, independent component analysis is used to deal with the denoising of corrosion acoustic emission signals of tank bottom in this paper. In the paper, acoustic emission signals of double exponential model is respectively mixed with white noise signals and stochastic noise signals, and acoustic emission sources and disturbance sources are respectively represented by double exponential model of acoustic emission signals and noise signals, which are independent on statistics, and then FastICA is used to simulation analysis, which is successful to identify acoustic emission signals and white noise signals. The results demonstrate that fastICA is effective to denoise acoustic emission signals.

• Periodical: Applied Mechanics and Materials (Volume 142)
• Pages: 180-183
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.142.180
• Online since: November 2011
• Authors: Yang Yu, Jia Zhao
• Keywords: Acoustic Emission (AE), De-Noising, Independent Component Analysis (ICA)

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