Study on Corrosion Acoustic Emission Separation Based on Blind Source Separation

Yang Yu; Xiang Zhou

doi:10.4028/www.scientific.net/AMR.503-504.1597

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 503-504Study on Corrosion Acoustic Emission Separation...

Study on Corrosion Acoustic Emission Separation Based on Blind Source Separation

Abstract:

When corrosion signals of tank bottom is detected by online method, it is essential to identify corrosion signals of different corrosion pots. It is a new method based on blind source separation. Blind source separation has produced many arithetics, among which entropy maximization is more mature. The aim of this paper is to separate corrosion signals by using entropy maximization arithmetic. Furthermore, the separation of linear mixed acoustic emission signals is achieved through simulation. The results indicate that blind source separation is an effective method for the separation of corrosion signals.

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Periodical:

Advanced Materials Research (Volumes 503-504)

Pages:

1597-1600

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.503-504.1597

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Online since:

April 2012

Authors:

Yang Yu, Xiang Zhou

Keywords:

Blind Source Separation, Bottom-Line Detection of Tanks, Corrosion Signal Processing, Entropy Maximization Algorithm

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References

[1] Kaewtrakulpong P. Study on source location using an acoustic emission system for various corrosion types. NDT&E International, 2007, (40): 584-593.

DOI: 10.1016/j.ndteint.2007.05.003

Google Scholar

[2] Geng RS. Prediction of fatigue crack initiation of aircraft using AE. Proc of international Conference on Failure Analysis And Prevention, Beijing: 1995, 1535-1539.

Google Scholar

[3] Mirakowski. Application acoustic emission in evaluation of pitting corrosion in steel[J]. JCM, 2002, 2(1): 111-117.

Google Scholar

[4] Physical Acoustic Corporation. SAMOS AE System User's Manual. American, Letters, 2008. 27(18): 139-144.

Google Scholar

[5] Jirarungsatean, Prateepasen A, Thungsuk P. Corrosion monitoring using acoustic mission[J]. Science Material Technology, 2002, 2(15): 2-4.

Google Scholar

[6] P. T. Cole. Connell valuation Lined Aboveground Storage Tank Bottoms the Floor Condition User's Manual. Evaluation of the tank Integrity Technical Report: TR-107-74-06/93.

Google Scholar

[7] Fregonese M, Idrissi H, Mazille H, et al. Initiation and propagation steps in pitting corrision of austenitic stainless steels: monitoring by acoustic emission[J]. Corission Science, 2001, 43(1): 627~641.

DOI: 10.1016/s0010-938x(00)00099-8

Google Scholar